Chapter 6: Rate-Distortion Theory

Learning Objectives

• Formulate the lossy compression problem with distortion measures
• Derive the rate-distortion function $R(D)$ and its properties
• Prove the rate-distortion theorem via the covering lemma
• Compute $R(D)$ for binary and Gaussian sources in closed form
• Understand reverse waterfilling for vector Gaussian sources
• Apply the Wyner-Ziv theorem for compression with decoder side information
• Connect rate-distortion theory to practical transform coding and quantization