7 December 1978 A Rate Distortion Analysis Of Adaptive Hybrid Picture Coding
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Proceedings Volume 0149, Digital Image Processing II; (1978); doi: 10.1117/12.956663
Event: 22nd Annual Technical Symposium, 1978, San Diego, United States
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.
© (1978) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
R. A. Jones, D. F. Mix, "A Rate Distortion Analysis Of Adaptive Hybrid Picture Coding", Proc. SPIE 0149, Digital Image Processing II, (7 December 1978); doi: 10.1117/12.956663; https://doi.org/10.1117/12.956663


Image processing

Autoregressive models

Computer programming

Digital image processing

Mathematical modeling

Process modeling


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