Image Compression Technique Used By Bio-Inspired Tsa Optimized Algorithm For Enlarge Memory Management

Abstract

The well-known classical image compression algorithms are renowned for their outstanding performance, low computational complexity, and production of an embedded bitstream that can be decoded at different bit rates with progressively better picture quality  more bits are received. It takes a lot of computer memory since it stores the created sets and the pixel locations in linked lists. The transform's multiresolution capability does not lead to the generation of a resolution-scalable bitstream that would enable different resolutions to decode the image. The TSA Optimized Discrete Wavelet Transform approach, which only needs one list of fixed size measuring 1/4 the size of the image and an average of 2.25 bits/pixel, solves the massive memory problem of traditional techniques. The study's main contribution is to scale up image quality and resolution in order to free up more memory. The TSA Optimized Discrete Wavelet Transform approach is recommended in this study to decrease complexity and increase speed. Due to the algorithm's special characteristics, it is ideal for addressing the different skills and resolution-related preferences of today's Internet users.