IMAGE AND VIDEO COMPRESSION - 2020/1
Module code: EEEM011
In light of the Covid-19 pandemic the University revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. Further information on changes made to modules during the 2020/21 academic year can be found here: https://www.surrey.ac.uk/coronavirus/course-changes-old
Due to the volume of changes made during the 2020/21 academic year this means that some information within the programme and module catalogue had been amended. Please ensure that you are viewing your modules alongside the module changes page. If you have any queries you are invited to contact the relevant Programme Leader or Academic Hive with any questions relating to the information available.
Expected prior learning: None specifically advised.
Module purpose: This module introduces basic notions of rate-distortion theory applied to the compression of digitised still images and moving sequences, provides high-level descriptions of mainstream algorithms for coding and error resilience and offers an overview of the main features, components and algorithmic tools involved in current international standards for image and video compression and error resilience in multimedia applications.
Electrical and Electronic Engineering
FERNANDO Anil (Elec Elec En)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: I200
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 105
Lecture Hours: 11
Laboratory Hours: 12
Prerequisites / Co-requisites
Indicative content includes the following.
Component Coding Algorithms,
Lecturers: FERNANDO WAC Dr and BOBER MZ Prof
30 Lecture hours with Problem Classes
 Introduction - Key terminology and fundamental concepts of digital video coding. Historical evolution of coding standards.
 Digital video – Coding operation in the image chain. Coding of color signal. Digital video formats. The effects of scanning and colour coding in television systems, digital video sampling formats. Recommendation ITU-R BT. 601.
[3-4] Principles of digital signal compression – Self-information, entropy, rate/distortion, sources with and without memory, coding theorems, practical assessment of objective and subjective quality, Recommendation ITU-R BT. 500.
[5-8] Basic coding techniques for still images and video sequences – Predictive coding, transform coding, scalar and vector quantisation, subband/wavelet coding, interframe coding, motion estimation and motion-compensated prediction.
[9-10] Image coding Standards – The JPEG specification; baseline, progressive, hierarchical and lossless coding.
[11-15] Video coding Standards – The MPEG-1/2 family of specifications; profiles and levels, coding of progressive and interlaced video, motion compensation modes, the main profile/main level coding algorithm, H.264 AVC/SVC, HEVC, scalability.
[16-1] Other video coding techniques – MPEG-4, distributed coding
[17-19] Emerging and Future Video Coding Technologies: Video coding for 3D, Multi-view video, HDR Video Coding, UHDTV
 Problem Class.
 Introduction to Video Communication
[22-23] Aspects of error resilience in video coders – Different effects of bit errors on video data – Loss of synchronisation.
[24-25] Error concealment strategies - Zero-redundancy techniques. Motion vector recovery algorithms. INTRADC coefficients interpolation. Limitations of error concealment techniques.
 Packet video transmissions –Effects of packetisation schemes of compressed video on error performance.
[27-28] Robustness of video coders – Effects of video information loss. Error sensitivity of various video parameters. Robustness improvement using prioritised information loss. Robustness improvement using local feedback loop. Quality of Experience (QoE).
[29-30] Error resilience schemes in video coders – INTRA Refresh. AIR. Backward channel signalling. Data partitioning. EREC – Two-way Decoding and RVLC.
|Assessment type||Unit of assessment||Weighting|
|Practical based assessment||LABORATORY||15|
Not applicable: students failing a unit of assessment resit the assessment in its original format.
The assessment strategy for this module is designed to provide students with the opportunity to demonstrate the learning outcomes. The written examination will assess the knowledge and assimilation of terminology, concepts and theories of image and video compression, as well as the ability to analyse state-of-the-art image and video codecs and how to use them for present communications systems. The design assignment will assess the ability to design video communications systems, including the related technical skills acquired in the laboratory work.
Thus, the summative assessment for this module consists of the following.
· 2-hour, closed-book written examination
· Image and Video Codec design. A multi-part assignment involving the design of a image and video system, as assessed by a final technical report (10-20 pages), that has to be submitted by Tuesday of Week 10.
Note that any deadline given here is indicative. For confirmation of exact date and time, please check the Departmental assessment calendar issued to you.
Formative assessment and feedback
For the module, students will receive formative assessment/feedback in the following ways.
· During lectures, by question and answer sessions
· Being a part of the interactive lectures
· During lectures, by problem solving
· During tutorials/tutorial classes
· During supervised laboratory sessions
· During supervised computer laboratory sessions
· Via the marking of written reports
· Via assessed coursework
- to provide an understanding of the principles underlying the compression of image and video signals
- to provide in-depth knowledge of state-of-the-art coding techniques, internationally standardised compression algorithms, error resilience techniques and related systems and technology.
|1||Demonstrate a coherent and systematic understanding of the main concepts in image and video compression. .||CT|
|2||Work with theoretical and research based knowledge in image and video coding.||KPT|
|3||Critically evaluate, utilise and develop state-of-the-art coding techniques for future media applications||KCPT|
|4||Contribute to the identification, analysis and solution of complex problems, the enhancement of the performance of existing systems and the design of novel algorithms and algorithmic tools.||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to achieve the specified learning outcomes by teaching the module syllabus in lectures, and supporting the assimilation and understanding of the taught material by the supervised lab classes. The practical design and technical skills related to the subject are acquired through coursework involving an assignment on image and video compression system design, and then the performance characterisation of the designed system through laboratory experiments.
Learning and teaching methods include:
- Lectures: 10 weeks, 3 hours per week.
- Design Labs: Image and Video Codec design. This design assignment is based on laboratory sessions that take place for five weeks, from Week 5 to Week 9. These provide the technical skills and expertise required for performance characterisation of state-of-the-art image and video systems. Students then have to produce a technical report that is submitted in Week 10 (see below).
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: EEEM011
Programmes this module appears in
|Computer Vision, Robotics and Machine Learning MSc||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Electronic Engineering MSc||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Artificial Intelligence MSc||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Computer and Internet Engineering MEng||2||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Communication Systems MEng||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Electronic Engineering with Communications MEng||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Electronic Engineering with Audio-Visual Systems MEng||2||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Electronic Engineering with Computer Systems MEng||2||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Electronic Engineering MEng||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Electronic Engineering with Professional Postgraduate Year MSc||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2020/1 academic year.