Efficient reordering algorithm for color palette image using adaptive particle swarm technique
Palette re-ordering is a class of pre-processing methods aiming at finding a permutation of color palette such that the resulting image of indexes is more amenable for compression. The objective is to manipulate the palette index such that the adjacent symbols are assigned close indices in the symbol space, thus enhancing the compressibility of the image with many lossless compressors. Finding an exact reordered palette would certainly be exhaustive and computationally complex. To address this issue, a heuristic approach based on Traveling Salesman Problem formulation (NP hard) is sought. In this paper, the solution to this NP hard problem is presented by using an Adaptive Particle Swarm Optimization to achieve fast global convergence by maximizing the co-occurrences.
reindexing palette-indexed image particle swarm optimization (pso) adaptive particle swarm optimization (apso) traveling salesman problem (tsp) cross entropy (ce) non-deterministic polynomial-time hard (np-hard)