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Statistical evaluation of predictive data compression systems

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1 Author(s)
S. Werness ; Environmental Research Institute of Michigan, Ann Arbor, MI

A simple image reconstruction evaluation procedure has been developed for use in analysis and design of image compression systems. The evaluation consists of two parts: 1) examination of the autocorrelation function of the reconstruction errors, and 2) comparison of the distribution size and shape of the reconstructed image to that of the original. The philosophy behind the evaluation procedure is rooted in consideration of visual mechanisms and in linear system identification model validation techniques. Although originally postulated for use in the development of compression systems for noisy synthetic aperture radar (SAR) imagery for which the usual mean square error criterion is particularly useless, the evaluation procedure is proposed to be useful for analysis of any image compression system. The utility of the procedure is demonstrated with the selection of the best quantizer step sizes and data rates for an SAR predictive coding algorithm combined with a switched quantizer. It is also demonstrated with SAR data from which the speckle noise has been removed.

Published in:

IEEE Transactions on Acoustics, Speech, and Signal Processing  (Volume:35 ,  Issue: 8 )