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Image Quantization using HSI based on Bacteria Foraging Optimization
Bacteria Foraging Optimization a nature-inspired optimization has drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. Color image quantization is an important process of representing true color images using a small number of colors. Existing color reduction techniques tend to alter image color structure and distribution. Thus the researchers are always finding alternative strategies for color quantization. In cylindrical color spaces like HSI, color is represented by hue, saturation and intensity. These components are closer to the way human perceives and describes color. Hue, saturation and intensity can also reveal image features that are not so obvious in other color spaces. The objective of this research work, is to design an algorithm for Image Quantization using HSI color space based on Bacteria Foraging Optimization. To implement and test the proposed algorithm. To compare the designed algorithm with other quantization techniques. The conducted experiments indicate that proposed algorithm generally results in a significant improvement of image quality compared to other well-known approaches.
Keywords
Color Reduction, Bacteria Foraging Optimization, HSI Color Space, Euclidean Distance, Swarm Intelligence.
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