Published Paper Details:

Image Data compression finds application in picture compression, where it minimizes the number of bits required to represent an image compared to its original format. In order to store and transmit data efficiently, picture compression aims to decrease irrelevant and redundant image data. Therefore, picture compression may speed up transmission and decrease network latency.In employing a lossless compression technique, data remains intact throughout the compression process without any loss. This study introduces a novel three-stage lossless compression approach called Huffman Inspired LZW Lossless Compression of Images utilising Retinex Algorithm. The first step is to compress the picture using Huffman coding. The second step is to compress the data using LZW and then decode it after joining all of the Huffman code words. Stage three involves applying the Retinex algorithm to the compressed picture in order to boost contrast and overall image quality. Using this suggested method, you can improve MATLAB's compression rate (CR), or mean square error (MSE).