Image compression systems commonly operate by transforming the input signal into a new representation whose elements are then independently quantized. The success of such a system depends on two properties of the representation. First, the coding rate is minimized only if the elements of the representation are statistically independent. Second, the perceived coding distortion is minimized only if the errors in a reconstructed image arising from quantization of the different elements of the representation are perceptually independent. 

We argue that linear transforms cannot achieve either of these goals, and propose an adaptive non-linear image representation that greatly reduces both the statistical and the perceptual redundancy amongst representation elements. We develop an efficient method of inverting this representation, and we demonstrate through simulations that this dual reduction in dependency can greatly improve the visual quality of compressed images.

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