Color Image Histogram Equalization

MATLAB 268K 210 views 0 downloads 1 credits
Tags:

Resource Overview

Color Image Histogram Equalization: Split a color image into red, green, and blue channels, apply histogram equalization independently to each channel, then merge the three processed channels to achieve overall image enhancement. In code implementations, this typically involves using channel separation functions (like cv2.split()), applying histogram equalization algorithms to each channel matrix, and merging results (using cv2.merge()).

Detailed Documentation

Color image histogram equalization is an image enhancement technique. The algorithm separates a color image into red, green, and blue channels using color space decomposition. Each channel undergoes histogram equalization - a process that redistributes pixel intensities to maximize contrast by flattening the histogram distribution. The equalized channels are then recombined to produce an image with improved overall contrast and saturation. This method significantly enhances visual quality by making image details more distinguishable. Key implementation steps include calculating cumulative distribution functions for each channel and mapping original pixel values to new values using transfer functions. Due to its effectiveness in improving perceptual quality, color image histogram equalization finds wide applications in digital photography, medical imaging, and computer vision preprocessing pipelines.

You May Also Like