Investigation of row and column permutations for lossless compression of images

The focus of our present study is on exploring the use of permutation techniques to achieve better compression gains in lossless image compression. As invertible functions, permutations are suitable for use in lossless image compression. In this study, we investigate the problem of determining an optimal permutation of rows or columns of images to improve the standard lossless compression algorithms, such as JPEG. We first recast an optimal permutation as a Hamiltonian circuit problem of an appropriate complete graph. Then we use the Lin-Kernighan heuristic algorithm for the symmetric Traveling Salesman Problem to compute the desired circuit. We include performance results of our proposed algorithm on a set of test images.