Abstract
The purpose of color quantization is to reduce colors in an image with the least parody. Clustering is a popularly used method for color quantization. Color image quantization is an essential action in several applications of computer graphics and image processing. Most of the quantization techniques are mainly based on data clustering algorithms. In this paper, a color reduction hybrid algorithm is proposed by applying Jaya algorithm for clustering. We examine the act of Jaya algorithm in the pre-clustering stage and K-means in the post-clustering phase, and the limitations of both the algorithms are overcome by their combination. The algorithms are compared by MSE and PSNR values of the four images. The MSE values are lower and PSNR values are higher for the proposed algorithm. The results explain that the proposed algorithm is surpassed both the K-means clustering and Jaya algorithm clustering for color reduction method.
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