Advanced Color Images Enhancement Using Wavelet and K-means Clustering

In this paper, we are proposing a new method of enhancing contrast of color images based on human visual system. In this method we convert the RGB (Red, Green, and Blue) values of each pixel of any segment of the original image to HSV (Hue, Saturation, and Value) values. Then we segment the V component of the original image into the dark and bright parts using k-means image segmentation technique. Next we apply (again to each segment: dark and bright) the wavelet transform to the luminance value V component of the color image to get the approximate component which is converted by applying grey-level contrast enhancement technique based on human visual system. Then, inverse wavelet transform is performed on the converted coefficients so that the enhanced V values are obtained. The saturation components are enhanced by histogram equalization. The H components are not changed, because changes in the H components could degrade the color balance between the HSV components. The enhanced S and V together with H are converted back to RGB values. Our new method has effectively achieved a successful enhancement of any color images considering their darkness or their low contrast by taking any image as a whole and then dividing it into its dark and bright segments.