Calculation of Image Contrast in MATLAB

This file contains multiple images with varying contrast levels. Image contrast refers to the degree of brightness difference between different regions in an image. Calculating image contrast is a fundamental image processing technique used to evaluate image clarity and visual quality. Through contrast computation, we can analyze details and edges within images, enabling effective image enhancement and optimization. Therefore, understanding and calculating image contrast is essential when working with image processing tasks.

In MATLAB, contrast calculation can be implemented using various approaches: The standard deviation method calculates contrast by computing the standard deviation of pixel intensities, where higher values indicate greater contrast. The Michelson contrast formula ((max-min)/(max+min)) is suitable for periodic patterns, while the RMS contrast provides a global contrast measure. Key MATLAB functions for contrast analysis include std2() for matrix standard deviation, max() and min() for intensity range detection, and contrast() from the Image Processing Toolkit for specialized contrast measurements.

Implementation typically involves reading images using imread(), converting to grayscale with rgb2gray() if necessary, and applying contrast calculation algorithms. For image enhancement, histogram equalization via histeq() or adaptive histogram equalization using adapthisteq() can significantly improve contrast by redistributing pixel intensities.