Foundation of Video Coding



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skalyar va vektorli kvantlash 3 lab

Summary

  • ©Yao Wang, 2003
  • Coding: Quantization
  • Coding system:
  • Quantization:
    • Scalar quantization:
      • Uniform quantizer
      • MMSE quantizer (Nearest neighbor and centroid condition)
    • Vector quantization
    • Uniform quantizer
      • Can be realized by lattice quantizer (not discussed here)
  • Rate distortion characterization of lossy coding
    • Bound on lossy coding
    • Operational RD function of practical quantizers

Homework 8

  • ©Yao Wang, 2003
  • Coding: Quantization
  • Reading assignment:
    • Sec. 8.5-8.7, 8.3.2,8.3.3
  • Written assignment
    • Prob. 8.8,8.11,8.14
  • Computer assignment
    • Option 1: Write a program to perform vector quantization on a gray scale image using 4x4 pixels as a vector. You should design your codebook using all the blocks in the image as training data, using the generalized Lloyd algorithm. Then quantize the image using your codebook. You can choose the codebook size, say, L=128 or 256. If your program can work with any specified codebook size L, then you can observe the quality of quantized images with different L.
    • Option 2: Write a program to perform color quantization on a color RGB image. Your vector dimension is now 3, containing R,G,B values. The training data are the colors of all the pixels. You should design a color palette (i.e. codebook) of size L, using generalized Lloyd algorithm, and then replace the color of each pixel by one of the color in the palette. You can choose a fixed L or let L be a user-selectable variable. In the later case, observe the quality of quantized images with different L.

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