Computation-rate-distortion in transform coders for image compression

Abstract

We consider the computational complexity of block transform coding and tradeoffs among computation, bit rate, and distortion. In particular, we illustrate a method of coding that allows decompression time to be traded with bit rate under a fixed quality criteria, or allows quality to be traded for speed with a fixed average bit rate. We provide a brief analysis of the entropy coded infinite uniform quantizer that leads to a simple bit allocation for transform coefficients. Finally, we consider the computational cost of transform coding for both the discrete cosine transform (DCT) and the Karhunen-Loeve transform (KLT). In general, a computation-rate- distortion surface can be used to select the appropriate size transform and the quantization matrix for a given bandwidth/CPU channel.