Histogram Equalization of Color Images in RGB and HSV Color Spaces

For input color images, histogram equalization is performed in both RGB and HSV color spaces, with comparative display of the equalization effects. Histogram equalization is a method used to enhance image contrast by redistributing the gray levels of image pixels, resulting in more uniform overall brightness and clearer image details. In the RGB color space, histogram equalization can be applied separately to the red, green, and blue channels, typically implemented using functions like cv2.equalizeHist() for each channel. In the HSV color space, equalization is performed specifically on the value (brightness) channel while preserving the hue and saturation components to maintain color integrity. The comparison between pre-equalization and post-equalization images allows for visual assessment of the enhancement effects, facilitating further image processing and analysis. The implementation typically involves color space conversion using cv2.cvtColor(), channel separation, equalization processing, and channel recombination to generate the final enhanced images.