Foundation of Video Coding

• Foundation of Video Coding
• Part II: Scalar and Vector Quantization

• Yao Wang
• Polytechnic University, Brooklyn, NY11201
• [e-mail]

• Video Processing & Communications

• Based on: Y. Wang, J. Ostermann, and Y.-Q. Zhang, Video Processing and Communications, Prentice Hall, 2002.

Outline

• ©Yao Wang, 2003

• Coding: Quantization

• Overview of video coding systems
• Scalar Quantization
• Vector Quantization
• Rate-distortion characterization of lossy coding
• Operational rate distortion function
• Rate distortion bound (lossy coding bound)

Components in a Coding System

• ©Yao Wang, 2003

• Coding: Quantization

Lossy Coding

• ©Yao Wang, 2003

• Coding: Quantization

• Original source is discrete
• Lossless coding: bit rate >= entropy rate
• One can further quantize source samples to reach a lower rate
• Original source is continuous
• Lossless coding will require an infinite bit rate!
• One must quantize source samples to reach a finite bit rate
• Lossy coding rate is bounded by the mutual information between the original source and the quantized source that satisfy a distortion criterion
• Quantization methods
• Scalar quantization
• Vector quantization

Scalar Quantization

• ©Yao Wang, 2003

• Coding: Quantization

• General description
• Uniform quantization
• MMSE quantizer
• Lloyd algorithm

SQ as Line Partition

• ©Yao Wang, 2003

• Coding: Quantization