The likelihood term in restoration of transform-compressed imagery
Mark A. Robertson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Compression of imagery by quantization of the data's transform coefficients introduces an error in the imagery upon decompression. When processing compressed imagery, often a likelihood term is used to provide a statistical description of how the observed data are related to the original noise-free data. This work derives the statistical relationship between compressed imagery and the original imagery, which is found to be embodied in a (in general) non-diagonal covariance matrix. Although the derivations are valid for transform coding in general, the work is motivated by considering examples for the specific cases of compression using the discrete cosine transform and the discrete wavelet transform. An example application of motion-compensated temporal filtering is provided to show how the presented likelihood term might be used in a restoration scenario.