Image compression method based on multi-scale decomposition with increased weights in spline layer nodes

Abstract

The article is devoted to the development and improvement of image compression methods. Information compression is critically important in the modern digital world, as the volume of data is constantly growing, and effective management of this data is becoming more and more relevant. To solve this problem, algorithms have been created that allow performing a compression operation with the loss of a certain amount of information (Lossy) or without loss (Lossless). This article focuses on the development of a lossy compression method, where less noticeable data is removed, which gives a high compression ratio, but leads to a decrease in quality (for example, JPEG, fractal, some MPEG methods). The main task of scientists is to find such an algorithmic solution that will allow, at a higher compression ratio, to leave the highest possible image quality. The main mathematical apparatus that provides lossy compression is the discrete cosine transform (DCT) or wavelet methods for converting pixels into the time domain. The authors proposed to use a different approach, namely, in the process of multiscale decomposition, to use spline functions as the basis function instead of wavelets. Accordingly, a spline multiscale decomposition with increased weights in the spline gluing nodes was developed. The advantages of such an algorithm in comparison with the direct procedure of spline multiscale decomposition and with known image compression standards were also evaluated.