Performance Analysis of Image Compression Using Fuzzy Logic Algorithm

Abstract

With the increase in demand, product of multimedia is increasing fast and thus contributes to insufficient network bandwidth and memory storage. Therefore image compression is more significant for reducing data redundancy for save more memory and transmission bandwidth. An efficient compression technique has been proposed which combines fuzzy logic with that of Huffman coding. While normalizing image pixel, each value of pixel image belonging to that image foreground are characterized and interpreted. The image is sub divided into pixel which is then characterized by a pair of set of approximation. Here encoding represent Huffman code which is statistically independent to produce more efficient code for compression and decoding represents rough fuzzy logic which is used to rebuilt the pixel of image. The method used here are rough fuzzy logic with Huffman coding algorithm (RFHA). Here comparison of different compression techniques with Huffman coding is done and fuzzy logic is applied on the Huffman reconstructed image. Result shows that high compression rates are achieved and visually negligible difference between compressed images and original images.