With the ever increasing demand for image transmission and image storage, various algorithms for image data compression have been developed. 1 To transmit pictures at lower bandwidth or to minimize the memory size for storage, the image must be compressed by the removal of redundant information. Transform image coding has been proven to be an efficient method for image compression.2,3 In the basic transform image coding concept, an image is divided into small blocks of pixels and each block undergoes a two-dimensional transformation to produce an equal-sized array of transform coefficients. The coding process is then performed on the transformed block image. It has been shown that the compression factor of the discrete cosine transform (DCT) compares closely with that of the Karhunen-Loeve transform, which is considered to be the optima1.4 But, comparatively, using the fast cosine transform (FCT) algorithm, the implementation of DCT is much simpler. Therefore, in many transform coding systems a large amount of digital hardware is dedicated to perform the 2-D FCT, because it is believed to be the only practical approach to get close to optimal performance. This consideration leads the recent research efforts on the transform image coding concentrated on the improvement of the coding process only.