Lossless Encoding Method Based on a Mathematical Model and Mapping Pixel Technique for Healthcare Applications

Abstract

The compression system typically comprises two fundamental categories: compression and decompression. Within the realm of compression, there exist two primary types: lossy compression and lossless compression. In this research, a novel lossless digital image encoding technique is presented. This method depends on performing a series of iterative mathematical transformations. The methodology of performing this method is similar to the process of performing the fractal compression algorithm, with an essential difference: the fractal pressure is classified as lossy compression, but this new method is lossless compression. It is well known that lossless compression methods produce higher-quality images than lossy methods, but they do not achieve as high a compression ratio as lossy methods. This research has overcome this problem. A high compression ratio has been obtained with images retrieved entirely according to the original (lossy). Lossless compression holds immense significance across a spectrum of applications, especially in critical domains such as healthcare, where the imperative is to retrieve images that are indistinguishable from the originals. ‎