Color quantization by partical swarm optimization algorithm, differential evolution algorithm and grey wolf algorithm
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Abstract (EN)
Color Quantization is used to reduce the number of colors in an image palette. This process results with shorter codes for each color used in output image in return, it provides compression. However this process is lossy and strongly effects image quality. As the palette size decreases, image quality detoriates as well. There are various deterministic algorithms; Uniform Color Quantizing, Median Cut, Octree, etc. for color quantization. Nature inspired algorithms ,however, are not widely studied for quantization purposes. In this thesis, it is aimed to employ some of nature inspired algorithms; Partical Swarm Optimization, Differential Evolution and Grey Wolf Optimization for color quantizing problem. Implementation details and performance comparisions can be found in the thesis. Keyword: Color Quantizing, PSO, GWO, DE
Author
Fatma Özyurt
How to Cite
Fatma Özyurt (Master Thesis). Color quantization by partical swarm optimization algorithm, differential evolution algorithm and grey wolf algorithm, 2017, Çukurova University.
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