CS 584 / CMPE 584 Multimedia Communication Image & Video Compression Lecture # 3 Shahab Baqai LUMS
Outline � Motivation for compression � Brief review of generic compression system – Use of transforms for representing a signal � Image compression – Transform, uniform quantization, Huffman coding � Video compression – Exploit temporal dimension of video signal – Motion-compensated prediction – Generic (MPEG-type) video coder architecture 2
Motivation for Compression: Example of HDTV Video Signal 3
4 Achieving Compression
Spatial and Temporal Redundancy 5
Generic Compression System 6
Generic Compression System (cont.) 7
Generic Compression System (cont.) 8
Representations: Transform and Subband Filtering Methods 9
10 Transform Image Coding
Possible Transforms for Image Coding 11
Global DCT versus Block DCT 12
Discrete Cosine Transform (DCT) 13
2-D Discrete Cosine Transform 14
Coding Transform Coefficients 15
Comments on Transform & Subband Filtering Methods 16
Transform/Subband Representations: Wavelet Transform 17
18 Image Compression
19 Transform/Subband Methods Spatial Processing
20 Spatial Processing Block DCT
21 Color Space Processing
22 Color Space Processing
Image Coding – Partial Summary 23
Quantization of DCT Coefficients 24
Runlength Coding and Zigzag Scanning of DCT Coefficients 25
Example: Runlength Coding and Zigzag Scanning of DCT Coefficients 26
Image Compression: Summary 27
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