Graduate School and Research Center in Digital Sciences

Image Coding

[ImCod]
T Technical Teaching


Abstract

Because multimedia data (in particular image and video) require efficient compression techniques in order to be stored and delivered, image and video compression is a crucial element of an effective communication system.

This course covers the most popular lossless and lossy formats, introduces the key techniques used in source coding, as well as appropriate objective/subjective metrics for visual quality evaluation. 

Teaching and Learning Methods:

Each class includes a problem session for students to practice the material learned.

This course includes a limited number of lab session hours.

Course Policies: It is mandatory to attend lab. sessions.

Bibliography

- Standard codecs: Image compression to advanced video coding Ghanbari, Mohammed Institution of Electrical Engineers (IEE) - 06/2003 - 430 p. 

- Compression et codage des images et des vidéos Barlaud, Michel and Labit, Claude Hermes.

Requirements

It would be good if you already have some knowledge about signal/image processing and Matlab, but it is not mandatory.

Description

The course covers the following techniques, standards and metrics: 

  • Techniques:

- Entropic coding, Huffman Coding

- Run Length Encoding

- Dictionary data based compression

- Predictive Coding

- Discrete Cosine Transform

- Block-matching

- Vector Quantization

- Wavelets

- Fractals. 

  • Standards:

- fax

- GIF, JPEG, JPEG2000

- H.26x, MPEG-x (1, 2, 4); HEVC.

  •  Metrics:

- RMSE, PSNR

- wPSNR, SSIM

Learning outcomes: 

Become familiar with major image and video formats.

Nb hours: 21.00

Grading Policy:  Quiz (25%), Final Exam (75%)