Engineering Tripos Part IIB, 4F12: Computer Vision, 2022-23
Module Leader
Lecturers
Prof R Cipolla and Dr Ignas Budvytis
Timing and Structure
Michaelmas term. 16 lectures (including 3 examples classes). Assessment: 100% exam
Aims
The aims of the course are to:
- introduce the principles, models and applications of computer vision.
- cover image structure, projection, stereo vision, structure from motion and object detection and recognition.
- give case studies of industrial (robotic) applications of computer vision, including visual navigation for autonomous robots, robot hand-eye coordination and novel man-machine interfaces.
Objectives
As specific objectives, by the end of the course students should be able to:
- design feature detectors to detect, localise and track image features.
- model perspective image formation and calibrate single and multiple camera systems.
- recover 3D position and shape information from arbitrary viewpoints;
- appreciate the problems in finding corresponding features in different viewpoints.
- analyse visual motion to recover scene structure and viewer motion, and understand how this information can be used in navigation;
- understand how simple object recognition systems can be designed so that they are independent of lighting and camera viewpoint.
- appreciate the commerical and industrial potential of computer vision but understand its limitations.
Content
- Introduction (1L)
Computer vision: what is it, why study it and how ? The eye and the camera, vision as an information processing task. Geometrical and statistical frameworks for vision. 3D interpretation of 2D images. Applications.
- Image structure (4L)
Image intensities and structure: edges, corners and blobs. Edge detection, the aperture problem and corner detection. Image pyramids, blob detection with band-pass filtering. The SIFT feature descriptor for matching. Characterising textures.
- Projection (4L)
Orthographic projection. Planar perspective projection. Vanishing points and lines. Projection matrix, homogeneous coordinates. Camera calibration, recovery of world position. Weak perspective and the affine camera. Projective invariants.
- Stereo vision and Structure from Motion (2L)
Epipolar geometry and the essential matrix. Recovery of depth by triangulation. Uncalibrated cameras and the fundamental matrix. The correspondence problem. Structure from motion. 3D shape examples from multiple view stereo.
- Deep Learning for Computer Vision (5L)
Basic architectures for deep learning in computer vision. Object detection, classification and semantic segmentation. Object recognition, feature embedding and metric learning. Transformers for computer vision and self-supervised learning.
- Example classes
Discussion of examples papers and past examination papers will be integrated with lectures.
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 11/11/2022 12:19
Engineering Tripos Part IIB, 4F8: Image Processing & Imaging Coding, 2019-20
Module Leader
Lecturers
Timing and Structure
Lent term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1 assumed; 3F3, 3F7 useful
Aims
The aims of the course are to:
- introduce the key tools for performing sophisticated processing of images by digital hardware
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the main elements of 2-dimensional linear system theory.
- design linear spatial filters for a variety of applications (smoothing etc)
- understand techniques for the restoration and enhancement of degraded images.
- show familiarity with the main characteristics of the human visual system with particular reference to subjective criteria for image data compression.
- understand techniques for image coding using transform methods including the Discrete Cosine Transform (as used in the JPEG coding standard) and overlapped transforms.
- understand methods for coding transform coefficients to provide maximum data compression.
Content
Sophisticated processing of images by digital hardware is now fairly common, and ranges from special effects in video games to satellite image enhancement. Three of the main application areas are video data compression, image enhancement, and scene understanding. This module introduces the key tools for performing these tasks, and shows how these tools can be applied. The module will be split into two courses of 8 lectures each: Image Processing, and Image Coding. Lectures are supported by computer demonstrations. There will be one examples sheet for each of the two 8-lecture sections.
Image Processing (8L, Dr J Lasenby)
This course covers the following topics, relevant to most aspects of image processing:
- Two-dimensional linear system theory, as applied to discretely sampled systems:
- The continuous 2D Fourier transform and its properties
- Digitisation, sampling, aliasing and quantisation
- The discrete 2D Fourier transform (DFT)
- 2D Digital Filters and Filter Design
- Zero phase filters
- Ideal 2D filters: rectangular and bandpass
- Filter design: the window method
- Image Deconvolution
- Deconvolution of noiseless images -- the inverse filter
- The Wiener filter (conventional and Bayesian derivations)
- Maximum Entropy deconvolution
- Image Enhancement
- Contrast enhancement
- Histogram equalisation
- Median filtering
Image Coding (8L, Prof N Kingsbury)
This course concentrates on image and video data compression techniques, and covers the following topics:
- Characteristics of the human visual system which are important for data compression:
- Spatial and temporal frequency sensitivities
- Distortion masking phenomena
- Luminance and colour (chrominance) processing
- 2D block transforms and wavelet transforms:
- Discrete cosine transforms
- Bi-orthogonal and orthonormal wavelet transforms
- Energy compaction properties of transforms for typical images
- Optimal quantisation techniques of coding transform coefficients for maximum data compression
- Huffman coding
- Run-length coding
- JPEG 2-dimensional run-size coding
- Video coding techniques
- Motion analysis
- Motion vector coding
- MPEG coding standards
Booklists
Please see the Booklist for Group F Courses for references for this module.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 28/05/2019 15:11
Engineering Tripos Part IIB, 4F8: Image Processing & Imaging Coding, 2018-19
Module Leader
Lecturers
Prof J Lasenby
Timing and Structure
Lent term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1 assumed; 3F3, 3F7 useful
Aims
The aims of the course are to:
- introduce the key tools for performing sophisticated processing of images by digital hardware
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the main elements of 2-dimensional linear system theory.
- design linear spatial filters for a variety of applications (smoothing etc)
- understand techniques for the restoration and enhancement of degraded images.
- show familiarity with the main characteristics of the human visual system with particular reference to subjective criteria for image data compression.
- understand techniques for image coding using transform methods including the Discrete Cosine Transform (as used in the JPEG coding standard) and overlapped transforms.
- understand methods for coding transform coefficients to provide maximum data compression.
Content
Sophisticated processing of images by digital hardware is now fairly common, and ranges from special effects in video games to satellite image enhancement. Three of the main application areas are video data compression, image enhancement, and scene understanding. This module introduces the key tools for performing these tasks, and shows how these tools can be applied. The module will be split into two courses of 8 lectures each: Image Processing, and Image Coding. Lectures are supported by computer demonstrations. There will be one examples sheet for each of the two 8-lecture sections.
Image Processing (8L, Dr J Lasenby)
This course covers the following topics, relevant to most aspects of image processing:
- Two-dimensional linear system theory, as applied to discretely sampled systems:
- The continuous 2D Fourier transform and its properties
- Digitisation, sampling, aliasing and quantisation
- The discrete 2D Fourier transform (DFT)
- 2D Digital Filters and Filter Design
- Zero phase filters
- Ideal 2D filters: rectangular and bandpass
- Filter design: the window method
- Image Deconvolution
- Deconvolution of noiseless images -- the inverse filter
- The Wiener filter (conventional and Bayesian derivations)
- Maximum Entropy deconvolution
- Image Enhancement
- Contrast enhancement
- Histogram equalisation
- Median filtering
Image Coding (8L, Prof N Kingsbury)
This course concentrates on image and video data compression techniques, and covers the following topics:
- Characteristics of the human visual system which are important for data compression:
- Spatial and temporal frequency sensitivities
- Distortion masking phenomena
- Luminance and colour (chrominance) processing
- 2D block transforms and wavelet transforms:
- Discrete cosine transforms
- Bi-orthogonal and orthonormal wavelet transforms
- Energy compaction properties of transforms for typical images
- Optimal quantisation techniques of coding transform coefficients for maximum data compression
- Huffman coding
- Run-length coding
- JPEG 2-dimensional run-size coding
- Video coding techniques
- Motion analysis
- Motion vector coding
- MPEG coding standards
Booklists
Please see the Booklist for Group F Courses for references for this module.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 03/08/2018 14:53
Engineering Tripos Part IIB, 4F8: Image Processing & Imaging Coding, 2020-21
Module Leader
Lecturers
Timing and Structure
Lent term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1 assumed; 3F3, 3F7 useful
Aims
The aims of the course are to:
- introduce the key tools for performing sophisticated processing of images by digital hardware
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the main elements of 2-dimensional linear system theory.
- design linear spatial filters for a variety of applications (smoothing etc)
- understand techniques for the restoration and enhancement of degraded images.
- show familiarity with the main characteristics of the human visual system with particular reference to subjective criteria for image data compression.
- understand techniques for image coding using transform methods including the Discrete Cosine Transform (as used in the JPEG coding standard) and overlapped transforms.
- understand methods for coding transform coefficients to provide maximum data compression.
Content
Sophisticated processing of images by digital hardware is now fairly common, and ranges from special effects in video games to satellite image enhancement. Three of the main application areas are video data compression, image enhancement, and scene understanding. This module introduces the key tools for performing these tasks, and shows how these tools can be applied. The module will be split into two courses of 8 lectures each: Image Processing, and Image Coding. Lectures are supported by computer demonstrations. There will be one examples sheet for each of the two 8-lecture sections.
Image Processing (8L, Dr J Lasenby)
This course covers the following topics, relevant to most aspects of image processing:
- Two-dimensional linear system theory, as applied to discretely sampled systems:
- The continuous 2D Fourier transform and its properties
- Digitisation, sampling, aliasing and quantisation
- The discrete 2D Fourier transform (DFT)
- 2D Digital Filters and Filter Design
- Zero phase filters
- Ideal 2D filters: rectangular and bandpass
- Filter design: the window method
- Image Deconvolution
- Deconvolution of noiseless images -- the inverse filter
- The Wiener filter (conventional and Bayesian derivations)
- Maximum Entropy deconvolution
- Image Enhancement
- Contrast enhancement
- Histogram equalisation
- Median filtering
Image Coding (8L, Prof N Kingsbury)
This course concentrates on image and video data compression techniques, and covers the following topics:
- Characteristics of the human visual system which are important for data compression:
- Spatial and temporal frequency sensitivities
- Distortion masking phenomena
- Luminance and colour (chrominance) processing
- 2D block transforms and wavelet transforms:
- Discrete cosine transforms
- Bi-orthogonal and orthonormal wavelet transforms
- Energy compaction properties of transforms for typical images
- Optimal quantisation techniques of coding transform coefficients for maximum data compression
- Huffman coding
- Run-length coding
- JPEG 2-dimensional run-size coding
- Video coding techniques
- Motion analysis
- Motion vector coding
- MPEG coding standards
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 01/09/2020 10:38
Engineering Tripos Part IIB, 4F8: Image Processing & Imaging Coding, 2024-25
Module Leader
Lecturers
Timing and Structure
Lent term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1 assumed; 3F3, 3F7 useful
Aims
The aims of the course are to:
- introduce the key tools for performing sophisticated processing of images by digital hardware
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the main elements of 2-dimensional linear system theory.
- design linear spatial filters for a variety of applications (smoothing etc)
- understand techniques for the restoration and enhancement of degraded images.
- show familiarity with the main characteristics of the human visual system with particular reference to subjective criteria for image data compression.
- understand techniques for image coding using transform methods including the Discrete Cosine Transform (as used in the JPEG coding standard) and overlapped transforms.
- understand methods for coding transform coefficients to provide maximum data compression.
Content
Sophisticated processing of images by digital hardware is now fairly common, and ranges from special effects in video games to satellite image enhancement. Three of the main application areas are video data compression, image enhancement, and scene understanding. This module introduces the key tools for performing these tasks, and shows how these tools can be applied. The module will be split into two courses of 8 lectures each: Image Processing, and Image Coding. Lectures are supported by computer demonstrations. There will be one examples sheet for each of the two 8-lecture sections.
Image Processing (8L, Dr J Lasenby)
This course covers the following topics, relevant to most aspects of image processing:
- Two-dimensional linear system theory, as applied to discretely sampled systems:
- The continuous 2D Fourier transform and its properties
- Digitisation, sampling, aliasing and quantisation
- The discrete 2D Fourier transform (DFT)
- 2D Digital Filters and Filter Design
- Zero phase filters
- Ideal 2D filters: rectangular and bandpass
- Filter design: the window method
- Image Deconvolution
- Deconvolution of noiseless images -- the inverse filter
- The Wiener filter (conventional and Bayesian derivations)
- Maximum Entropy deconvolution
- Image Enhancement
- Contrast enhancement
- Histogram equalisation
- Median filtering
Image Coding (8L, Prof N Kingsbury)
This course concentrates on image and video data compression techniques, and covers the following topics:
- Characteristics of the human visual system which are important for data compression:
- Spatial and temporal frequency sensitivities
- Distortion masking phenomena
- Luminance and colour (chrominance) processing
- 2D block transforms and wavelet transforms:
- Discrete cosine transforms
- Bi-orthogonal and orthonormal wavelet transforms
- Energy compaction properties of transforms for typical images
- Optimal quantisation techniques of coding transform coefficients for maximum data compression
- Huffman coding
- Run-length coding
- JPEG 2-dimensional run-size coding
- Video coding techniques
- Motion analysis
- Motion vector coding
- MPEG coding standards
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 31/05/2024 10:08
Engineering Tripos Part IIB, 4F8: Image Processing & Imaging Coding, 2022-23
Module Leader
Lecturers
Timing and Structure
Lent term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1 assumed; 3F3, 3F7 useful
Aims
The aims of the course are to:
- introduce the key tools for performing sophisticated processing of images by digital hardware
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the main elements of 2-dimensional linear system theory.
- design linear spatial filters for a variety of applications (smoothing etc)
- understand techniques for the restoration and enhancement of degraded images.
- show familiarity with the main characteristics of the human visual system with particular reference to subjective criteria for image data compression.
- understand techniques for image coding using transform methods including the Discrete Cosine Transform (as used in the JPEG coding standard) and overlapped transforms.
- understand methods for coding transform coefficients to provide maximum data compression.
Content
Sophisticated processing of images by digital hardware is now fairly common, and ranges from special effects in video games to satellite image enhancement. Three of the main application areas are video data compression, image enhancement, and scene understanding. This module introduces the key tools for performing these tasks, and shows how these tools can be applied. The module will be split into two courses of 8 lectures each: Image Processing, and Image Coding. Lectures are supported by computer demonstrations. There will be one examples sheet for each of the two 8-lecture sections.
Image Processing (8L, Dr J Lasenby)
This course covers the following topics, relevant to most aspects of image processing:
- Two-dimensional linear system theory, as applied to discretely sampled systems:
- The continuous 2D Fourier transform and its properties
- Digitisation, sampling, aliasing and quantisation
- The discrete 2D Fourier transform (DFT)
- 2D Digital Filters and Filter Design
- Zero phase filters
- Ideal 2D filters: rectangular and bandpass
- Filter design: the window method
- Image Deconvolution
- Deconvolution of noiseless images -- the inverse filter
- The Wiener filter (conventional and Bayesian derivations)
- Maximum Entropy deconvolution
- Image Enhancement
- Contrast enhancement
- Histogram equalisation
- Median filtering
Image Coding (8L, Prof N Kingsbury)
This course concentrates on image and video data compression techniques, and covers the following topics:
- Characteristics of the human visual system which are important for data compression:
- Spatial and temporal frequency sensitivities
- Distortion masking phenomena
- Luminance and colour (chrominance) processing
- 2D block transforms and wavelet transforms:
- Discrete cosine transforms
- Bi-orthogonal and orthonormal wavelet transforms
- Energy compaction properties of transforms for typical images
- Optimal quantisation techniques of coding transform coefficients for maximum data compression
- Huffman coding
- Run-length coding
- JPEG 2-dimensional run-size coding
- Video coding techniques
- Motion analysis
- Motion vector coding
- MPEG coding standards
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 24/05/2022 13:12
Engineering Tripos Part IIB, 4F8: Image Processing & Imaging Coding, 2023-24
Module Leader
Lecturers
Timing and Structure
Lent term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1 assumed; 3F3, 3F7 useful
Aims
The aims of the course are to:
- introduce the key tools for performing sophisticated processing of images by digital hardware
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the main elements of 2-dimensional linear system theory.
- design linear spatial filters for a variety of applications (smoothing etc)
- understand techniques for the restoration and enhancement of degraded images.
- show familiarity with the main characteristics of the human visual system with particular reference to subjective criteria for image data compression.
- understand techniques for image coding using transform methods including the Discrete Cosine Transform (as used in the JPEG coding standard) and overlapped transforms.
- understand methods for coding transform coefficients to provide maximum data compression.
Content
Sophisticated processing of images by digital hardware is now fairly common, and ranges from special effects in video games to satellite image enhancement. Three of the main application areas are video data compression, image enhancement, and scene understanding. This module introduces the key tools for performing these tasks, and shows how these tools can be applied. The module will be split into two courses of 8 lectures each: Image Processing, and Image Coding. Lectures are supported by computer demonstrations. There will be one examples sheet for each of the two 8-lecture sections.
Image Processing (8L, Dr J Lasenby)
This course covers the following topics, relevant to most aspects of image processing:
- Two-dimensional linear system theory, as applied to discretely sampled systems:
- The continuous 2D Fourier transform and its properties
- Digitisation, sampling, aliasing and quantisation
- The discrete 2D Fourier transform (DFT)
- 2D Digital Filters and Filter Design
- Zero phase filters
- Ideal 2D filters: rectangular and bandpass
- Filter design: the window method
- Image Deconvolution
- Deconvolution of noiseless images -- the inverse filter
- The Wiener filter (conventional and Bayesian derivations)
- Maximum Entropy deconvolution
- Image Enhancement
- Contrast enhancement
- Histogram equalisation
- Median filtering
Image Coding (8L, Prof N Kingsbury)
This course concentrates on image and video data compression techniques, and covers the following topics:
- Characteristics of the human visual system which are important for data compression:
- Spatial and temporal frequency sensitivities
- Distortion masking phenomena
- Luminance and colour (chrominance) processing
- 2D block transforms and wavelet transforms:
- Discrete cosine transforms
- Bi-orthogonal and orthonormal wavelet transforms
- Energy compaction properties of transforms for typical images
- Optimal quantisation techniques of coding transform coefficients for maximum data compression
- Huffman coding
- Run-length coding
- JPEG 2-dimensional run-size coding
- Video coding techniques
- Motion analysis
- Motion vector coding
- MPEG coding standards
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 30/05/2023 15:31
Engineering Tripos Part IIB, 4F8: Image Processing & Imaging Coding, 2017-18
Module Leader
Lecturers
Dr J Lasenby
Timing and Structure
Lent term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1 assumed; 3F3, 3F7 useful
Aims
The aims of the course are to:
- introduce the key tools for performing sophisticated processing of images by digital hardware
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the main elements of 2-dimensional linear system theory.
- design linear spatial filters for a variety of applications (smoothing etc)
- understand techniques for the restoration and enhancement of degraded images.
- show familiarity with the main characteristics of the human visual system with particular reference to subjective criteria for image data compression.
- understand techniques for image coding using transform methods including the Discrete Cosine Transform (as used in the JPEG coding standard) and overlapped transforms.
- understand methods for coding transform coefficients to provide maximum data compression.
Content
Sophisticated processing of images by digital hardware is now fairly common, and ranges from special effects in video games to satellite image enhancement. Three of the main application areas are video data compression, image enhancement, and scene understanding. This module introduces the key tools for performing these tasks, and shows how these tools can be applied. The module will be split into two courses of 8 lectures each: Image Processing, and Image Coding. Lectures are supported by computer demonstrations. There will be one examples sheet for each of the two 8-lecture sections.
Image Processing (8L, Dr J Lasenby)
This course covers the following topics, relevant to most aspects of image processing:
- Two-dimensional linear system theory, as applied to discretely sampled systems:
- The continuous 2D Fourier transform and its properties
- Digitisation, sampling, aliasing and quantisation
- The discrete 2D Fourier transform (DFT)
- 2D Digital Filters and Filter Design
- Zero phase filters
- Ideal 2D filters: rectangular and bandpass
- Filter design: the window method
- Image Deconvolution
- Deconvolution of noiseless images -- the inverse filter
- The Wiener filter (conventional and Bayesian derivations)
- Maximum Entropy deconvolution
- Image Enhancement
- Contrast enhancement
- Histogram equalisation
- Median filtering
Image Coding (8L, Prof N Kingsbury)
This course concentrates on image and video data compression techniques, and covers the following topics:
- Characteristics of the human visual system which are important for data compression:
- Spatial and temporal frequency sensitivities
- Distortion masking phenomena
- Luminance and colour (chrominance) processing
- 2D block transforms and wavelet transforms:
- Discrete cosine transforms
- Bi-orthogonal and orthonormal wavelet transforms
- Energy compaction properties of transforms for typical images
- Optimal quantisation techniques of coding transform coefficients for maximum data compression
- Huffman coding
- Run-length coding
- JPEG 2-dimensional run-size coding
- Video coding techniques
- Motion analysis
- Motion vector coding
- MPEG coding standards
Booklists
Please see the Booklist for Group F Courses for references for this module.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 31/05/2017 09:11
Engineering Tripos Part IIB, 4F5: Advanced Information Theory and Coding, 2025-26
Module Leader
Lecturer
Prof A Guillen i Fabregas and Dr Jossy Sayir
Timing and Structure
Lent term. 16 lectures. Assessment: 100% exam
Prerequisites
3F7 assumed, 3F1, 3F4 useful but not necessary
Aims
The aims of the course are to:
- Learn about applications of information theory to hypothesis testing as well as refinements of source and channel coding theorems through error exponents.
- Introduce students to the principles of algebraic coding and Reed Solomon coding in particular
- Give students an overview of cryptology with example of techniques that share the same mathematical background as algebraic coding.
Objectives
As specific objectives, by the end of the course students should be able to:
- have gained an appreciation for the connection between information-theoretic concepts and fundamental problems in statistics
- have a good understanding of the derivations of error exponents for data compression and transmission
- have a good understanding of the fundamental connections between hypothesis testing and information theory
- have gained a practical understanding of the algebraic fundamentals that underlie channel coding and cryptology
- understand the properties of linear block codes over finite fields
- be able to implement encoders and decoders for Reed Solomon codes
- have gained an overview of methods and aims in cryptology (including cryptography, crypt- analysis, secrecy, authenticity)
- be familiar with one example each of a block cipher and a stream cipher
- be able to implement public key cryptosystems, in particular the Diffie-Hellman and Rivest- Shamir-Adleman (RSA) systems
Content
-
This course will introduce students to applications of information theory and coding theory in statistics, information storage, and cryptography.
The first part of the course will discuss applications of information theory to universal data compression, statistics, and inference.
The second part of the course will expand linear coding principles acquired in 3F7 to non-binary codes over finite fields. After establishing the algebraic fundamentals, we will cover Reed-Solomon coding, a technique used in a wide range of communication and storage systems (hard disks, blu ray discs, QR codes, USB mass storage device class, DNA storage, and others.)
The final part of the course will introduce the discipline of cryptology, which includes cryptography, the essential art of ensuring secrecy and authenticity, and cryptanalysis, the dark art of breaking that secrecy. The course will cover a number of methods to provide secrecy, ranging from mathematically provable secrecy to public key methods through which computationally secure communication links can be established over public channels.
Information theory and statistics (7-9L, Prof Albert Guillén i Fàbregas)
- Source coding, optimum fixed-rate coding, error exponents
- Binary hypothesis testing, probability of error, error exponents, Stein's lemma
- M-ary hypothesis testing, probability of error
- Channel coding, connection with hypothesis testing, perfect codes, error exponents
Introduction to practical number theory and algebra (2-3L, Dr Jossy Sayir)
- Elementary number theory
- Groups and fields, extension fields
- 3 equivalent approaches to multiplication in extension fields
- Matrix operations and the Discrete Fourier Transform
Algebraic Coding (3L, Dr Jossy Sayir)
- Linear coding and the Singleton Bound
- Distance profiles and MacWilliams Identities
- Blahut’s theorem
- Reed Solomon (RS) codes
- Encoding and decoding of RS codes
Introduction to Cryptology (2L, Dr Jossy Sayir )
- Overview of cryptology
- Stream ciphers, examples
- Block ciphers, examples
- Public key cryptography, basic techniques
Further notes
Examples papers
Examples papers consist of a recommended list of problems to solve in the lecture notes.
Coursework
none
Booklists
- Information Theory:
- Elements of Information Theory, T. M. Cover & J. A. Thomas, Wiley-Interscience, 2nd Ed, 2006.
- Information Theory: Coding Theorems for Discrete Memoryless Systems, I. Csiszàr & J. Körner, Cambridge University Press, 2nd Ed. 2011.
- Coding theory:
- The Theory of Error-Correcting Codes, F. J. MacWilliams & N. J. A. Sloane, North Holland.
- Algebraic Codes for Data Transmission, Richard E. Blahut, Cambridge University Press, 2003 (Online 2012)
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 04/06/2025 13:30
Engineering Tripos Part IIB, 4F5: Advanced Information Theory and Coding, 2024-25
Module Leader
Lecturer
Prof A Guillen i Fabregas and Dr Jossy Sayir
Timing and Structure
Michaelmas term. 16 lectures. Assessment: 100% exam
Prerequisites
3F7 assumed, 3F1, 3F4 useful but not necessary
Aims
The aims of the course are to:
- Learn about applications of information theory to hypothesis testing as well as refinements of source and channel coding theorems through error exponents.
- Introduce students to the principles of algebraic coding and Reed Solomon coding in particular
- Give students an overview of cryptology with example of techniques that share the same mathematical background as algebraic coding.
Objectives
As specific objectives, by the end of the course students should be able to:
- have gained an appreciation for the connection between information-theoretic concepts and fundamental problems in statistics
- have a good understanding of the derivations of error exponents for data compression and transmission
- have a good understanding of the fundamental connections between hypothesis testing and information theory
- have gained a practical understanding of the algebraic fundamentals that underlie channel coding and cryptology
- understand the properties of linear block codes over finite fields
- be able to implement encoders and decoders for Reed Solomon codes
- have gained an overview of methods and aims in cryptology (including cryptography, crypt- analysis, secrecy, authenticity)
- be familiar with one example each of a block cipher and a stream cipher
- be able to implement public key cryptosystems, in particular the Diffie-Hellman and Rivest- Shamir-Adleman (RSA) systems
Content
-
This course will introduce students to applications of information theory and coding theory in statistics, information storage, and cryptography.
The first part of the course will discuss applications of information theory to universal data compression, statistics, and inference.
The second part of the course will expand linear coding principles acquired in 3F7 to non-binary codes over finite fields. After establishing the algebraic fundamentals, we will cover Reed-Solomon coding, a technique used in a wide range of communication and storage systems (hard disks, blu ray discs, QR codes, USB mass storage device class, DNA storage, and others.)
The final part of the course will introduce the discipline of cryptology, which includes cryptography, the essential art of ensuring secrecy and authenticity, and cryptanalysis, the dark art of breaking that secrecy. The course will cover a number of methods to provide secrecy, ranging from mathematically provable secrecy to public key methods through which computationally secure communication links can be established over public channels.
Information theory and statistics (7-9L, Prof Albert Guillén i Fàbregas)
- Source coding, optimum fixed-rate coding, error exponents
- Binary hypothesis testing, probability of error, error exponents, Stein's lemma
- M-ary hypothesis testing, probability of error
- Channel coding, connection with hypothesis testing, perfect codes, error exponents
Introduction to practical number theory and algebra (2-3L, Dr Jossy Sayir)
- Elementary number theory
- Groups and fields, extension fields
- 3 equivalent approaches to multiplication in extension fields
- Matrix operations and the Discrete Fourier Transform
Algebraic Coding (3L, Dr Jossy Sayir)
- Linear coding and the Singleton Bound
- Distance profiles and MacWilliams Identities
- Blahut’s theorem
- Reed Solomon (RS) codes
- Encoding and decoding of RS codes
Introduction to Cryptology (2L, Dr Jossy Sayir )
- Overview of cryptology
- Stream ciphers, examples
- Block ciphers, examples
- Public key cryptography, basic techniques
Further notes
Examples papers
Examples papers consist of a recommended list of problems to solve in the lecture notes.
Coursework
none
Booklists
- Information Theory:
- Elements of Information Theory, T. M. Cover & J. A. Thomas, Wiley-Interscience, 2nd Ed, 2006.
- Information Theory: Coding Theorems for Discrete Memoryless Systems, I. Csiszàr & J. Körner, Cambridge University Press, 2nd Ed. 2011.
- Coding theory:
- The Theory of Error-Correcting Codes, F. J. MacWilliams & N. J. A. Sloane, North Holland.
- Algebraic Codes for Data Transmission, Richard E. Blahut, Cambridge University Press, 2003 (Online 2012)
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 23/08/2024 18:37
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