Calendar Description:

Overview of multimedia communications system, basics of digital images and video, introduction to multimedia coding, entropy and information, rate distortion function, Huffman coding, arithmetic coding, run-length coding, Lempel-Ziv coding, quantization, JPEG compression, hybrid video coding, MPEG 4 and H.264 coding standards, transmission protocols (TCP/IP, RTP, RTSP) and channel modeling, error detection and erasure recovery, error concealment, multimedia security, watermarking.

Prereq Topics: Linear algebra, advanced calculus, and probability and statistics.

Prereqs: Level at least 4A Computer Engineering, Electrical Engineering, SYDE, MTE, BME, NE, or SE.

Tutorial Description: Questions and answers on material covered in lectures, specific help with current homework assignment, projects, and problem solving skills.

Project Description: Students will have opportunities to gain hands-on experience in compression algorithm implementation, and image/video processing and coding.

Hours per Week: LEC =3, TUT=1

Course Notes: Complete course notes will be available for download.

Reference books:

[1] P. Havaldar and G. Medioni, Multimedia  Systems: Algorithms, Standards, and Industry Practices. Course Technology, Cengage Learning, 2010. (ISBN-13: 978-1-4188-3594-1)

[2] Iain E.G. Richardson, H.264 and MPEG-4 Video Compression. New York: NY: Wiley, 2003.

[3] T. Acharya and A. K. Ray, Image Processing: Principles and Applications,

WileyInterScience, 2005.

Detailed Description:

Lectures

1

Introduction: overview of multimedia communications system and requirements; digital representation of image and video, image aspect ratio, color space and linear color transform, and YCrCb sampling formats; quality measurement; multiple resolution and description representation by source coding; multimedia security and watermarking; random sequence.

3

2

Fundamentals of lossless source coding: entropy, joint entropy, and conditional entropy; variable length codes and Kraft-McMillan inequality; source coding theorem; Huffman coding; universal source coding; run-length coding; arithmetic coding; Lempel-Ziv coding.

10

3

Introduction to lossy source coding: mutual information; information quantities for continuous random variables; rate distortion function; Gaussian rate distortion formula; quantization; Lloy-Max algorithm for designing optimal scalar quantizers.

4

4

Image and video coding: basic ideas of predictive coding and transform coding; Karhunen-Loeve (KL) transform; discrete cosine transform (DCT); JPEG standard and sequential DCT-based mode of operation; examples of multiple resolution coding: progressive DCT-based and hierarchical modes of JPEG; hybrid video coding; temporal prediction and motion compensation; overview of H.264 standard; the baseline profile of H.264 codec.

12

Transmission and recovery: Transmission protocols (OSI architecture, TCP/IP, UDP, RTP, RTSP); channel modeling; channel capacity; linear block codes; error detection; erasure recovery; error concealment.

7

Computer Experience: C, C++, or Matlab programming.

Lab Experience: None