Transform image coding with a new family of models

A set of adaptive transform coding schemes is developed that is based on a family of composite block source models for imagery. An iterative maximum-likelihood algorithm is developed for resolving model parameters from training set data. Both unconstrained (adaptive transform, adaptive quantization) and constrained (fixed transform, adaptive quantization) coders are obtained from the image model parameters. The resulting coders give excellent performance in coding test imagery at a variety of bit rates, and they consistently outperform the adaptive transform coders of W.H. Chen and C.H. Smith (1977). For example, a 2-dB improvement over the Chen and Smith scheme is obtained with a constrained coder with 128 classes operating at 0.5 bits/pixel. Computational limitations inhibit the design of unconstrained order with more than approximately 15 classes.<<ETX>>