Image data compression through a rectangular transform

Transform coding has been generally accepted as one of the best methods used for data compression. In transform processing, the image data is mapped into a new plane and the elements with minimum variances in this domain are discarded so as to get the data compression for a given quality. In this paper, a rectangular transform is defined for a given data compression. Studies made on different types of kernels show that the distortion is mainly due to rounding-off of the data on the transformed domain. This is minimized by proper selection of the inverse transform. Taking into consideration the correlation properties of the image, an optimization procedure is adopted to determine the best kernel. Results clearly indicate that the rectangular transform can be profitably used for a restricted class of pictures. © 1983 SPIE.