Histogram modification based lossy image compression scheme using Huffman coding

Medical images produce massive volumes of data, and consequently, suitable image compression procedures require to save expense and time of storage and transportation sequentially. The requirement of transferring or storing satellite images is increasing quickly with the evolution of advanced communications and imaging systems. In the digital world, the size of pictures is a major problem when dealing with the storage and transportation necessities. Compression is one of the most primary procedures to address this difficulty. The intention of data compression is to promote the storage and delivery of big images with excellent compression ratio and least distortion. Moreover, the number of internet user is growing day by day speedily. So, transferring of data is being an another significant concern. This article introduces histogram modification based lossy image compression using Huffman coding. A little bit change of pixel’s value is done which is why the number of probabilities of an original image is decreased and the value of probabilities are increased. As a result, Huffman coding uses very few bits in case of encoding and decoding than that of previous. This process provides higher compression ratio and less average code length keeping the same quality of the corresponding original image.