Сompression for texture images in different basis functions using system criteria analysis

Abstract

This paper considers image compression for texture images. For texture representation we consider the orthogonal decomposition of two-dimensional signals (images) using spectral transform in the different basis functions. This paper focuses on the analysis of the following basis DCT, FFT, Haar, Hartley, and Walsh using system criteria analysis. The error of the orthogonal representation of images and the computational cost are considered when choosing a basis system, which is based on the Bellman-Zadeh concept using fuzzy sets. It is shown that the Haar transform can represent textural images more efficiently with smaller average risk than other basis functions.