Function for Calculating Image Point-to-Region Grayscale Histograms

This text presents a MATLAB function implementation designed to calculate grayscale histograms that correlate individual image points with regional grayscale distributions. The function enables comprehensive analysis of grayscale dispersion patterns within images, facilitating deeper understanding of image characteristics. Key implementation features include pixel-wise grayscale extraction and regional aggregation algorithms that partition the image into designated areas. The function outputs grayscale values for each region and visualizes them through histogram representations, employing MATLAB's histogram plotting functions like histogram() or bar(). This granular visualization reveals detailed grayscale distribution variations across different image regions, providing critical data for subsequent image processing and analytical tasks. The implementation utilizes matrix operations for efficient pixel data handling and includes region segmentation logic using functions such as bwlabel() for connected component analysis. Through this function, researchers can systematically investigate image properties and features, establishing a robust foundation for advanced image processing and computer vision applications.