The approaches to achieving data compression when the source is a class of images have generally been variants of either unitary transform encoding or time domain encoding. Various hybrid approaches using DPCM in tandem with unitary transforms have been suggested. However, the problems of picture statistics dependence and error propagation cannot be solved by these approaches because the transformed picture elements form a non-stationary signal class. Naturally, a constant set of DPCM predictor coefficients cannot be optimal for all users. However, a composite non-stationary signal source can be decomposed into simpler subsources if it exhibits certain characteristics. Adaptive Hybrid Picture Coding (AHPC) is considered as a method of extracting these subsources from the composite sources in such a way that the over-all communication problem can be viewed as two different, but connected communication requirements. One requirement is the transmission of a set of sequences that are formed by the predictor coefficients. Each of these sequences forms a subsource. The additional requirement is the transmission of the error sequence. An intermediate fidelity requirement is presented which describes the effects of predictor parameter distortion on the transmission requirements for the error signal. The rate distortion bound on the channel requirements for the transmission of the predictor coefficients and the error signal is determined subject to a dual fidelity criterion. The signal class is a set of one dimensional unitary transformed images.