Nonlinear Transform Coding

Nonlinear Transform Coding with Lossless Polar Coordinates

In conventional transform coding, the importance of preserving desirable quantization partition cell shapes prevents one from considering the use of a nonlinear change of variables. If no linear transformation of a given source would yield independent components, this means having to encode it at a rate higher than its entropy, i.e. suboptimally. This thesis proposes a new transform coding tech...

The Coding-Optimal Transform

We propose a new transform coding algorithm that integrates all optimiza tion steps into a coherent and consistent framework Each iteration of the algorithm is designed to minimize coding distortion as a function of both the transform and quantizer designs Our algorithm is a constrained version of the LBG algorithm for vector quantizer design The reproduction vectors are constrained to lie at t...

Transform Coding of Images

Fractal coding versus classified transform coding

Fractal coding and classi ed transform coding exhibit strong structural similarity, but they use di erent types of redundancy in image data: piecewise self-similarity in one case and local correlation in the other. Comparing performance of the two techniques leads to a quantitative, compression-oriented de nition of piecewise self-similarity. The amount of piecewise self-similarity is evaluated...

Beyond Traditional Transform Coding

Beyond Traditional Transform Coding