RSIHE Algorithm (Recursive Sub-Image Histogram Equalization) with MATLAB Implementation and Technical Documentation

The RSIHE algorithm (Recursive Sub-Image Histogram Equalization) operates by recursively partitioning an image into 2^r equal-area sub-images, each undergoing independent histogram equalization. The MATLAB implementation typically involves key functions for image segmentation using recursive quadrant division, followed by histogram calculation and equalization for each sub-region using built-in functions like histeq or custom equalization routines. This algorithm effectively enhances image contrast and brightness while maintaining local characteristics, making it widely applicable across various domains including medical imaging, surveillance, and remote sensing. By processing each sub-image separately, RSIHE ensures appropriate enhancement for every image region, preventing over-enhancement in already balanced areas while improving poorly lit sections. The algorithm's flexibility allows parameter adjustment through the recursion depth parameter 'r', enabling customization for different scenarios. Higher r values create finer partitions for more localized enhancement, while lower values maintain broader regional characteristics. The MATLAB code includes configurable parameters for controlling the recursive depth, histogram bin sizes, and enhancement thresholds. The provided resources include complete MATLAB source code implementing the recursive partitioning logic and sub-image processing, a detailed research paper explaining the mathematical foundation, and sample images for testing. These materials support both research studies and practical applications in digital image processing, offering insights into adaptive histogram equalization techniques and their implementation.