ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Particle swarm optimization-based algorithms for TSP and generalized TSP
Information Processing Letters
On the relation between Memon's and the modified Zeng's palette reordering methods
Image and Vision Computing
On ordering color maps for lossless predictive coding
IEEE Transactions on Image Processing
A survey on palette reordering methods for improving the compression of color-indexed images
IEEE Transactions on Image Processing
Effective palette indexing for image compression using self-organization of Kohonen feature map
IEEE Transactions on Image Processing
Self Organizing Motor Maps for Color-Mapped Image Re-Indexing
IEEE Transactions on Image Processing
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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.