Coding of Image Residuals with Tailbiting Convolutional Codes and BCJR Decoding

  • Authors:
  • Mirek Novak

  • Affiliations:
  • -

  • Venue:
  • DCC '00 Proceedings of the Conference on Data Compression
  • Year:
  • 2000

Quantified Score

Hi-index 0.00

Visualization

Abstract

Image residuals are the high-dimensional part of a model-residual decomposition of still images. These residuals have been source encoded using Euclidean space representations of the codewords of tailbiting convolutional codes. The source coder represents each residual with the closest codeword of the code, using the BCJR decoding algorithm. It is shown that this technique is feasible if the probability distribution of the residuals can be adapted to suit the codeword distribution. Examples are given for two test images at rates 0.25 and 0.5 bits per pixel.