Image Enhancement Algorithms: Grayscale Transformation, Histogram Equalization, and Pseudocolor Enhancement

This article discusses an image enhancement algorithm based on grayscale transformation, histogram equalization, and pseudocolor enhancement techniques. The algorithm is implemented in MATLAB and demonstrates satisfactory performance results. The implementation typically involves MATLAB's Image Processing Toolbox functions, where grayscale transformation uses imadjust() for intensity mapping, histogram equalization employs histeq() for contrast enhancement, and pseudocolor enhancement applies colormap manipulation techniques to assign colors to different intensity ranges. However, it is important to note that while this algorithm has achieved some success, it still presents potential limitations. For instance, it may struggle with handling extreme image conditions and might require additional computational resources to achieve higher performance levels. Future research could explore algorithmic improvements through adaptive thresholding techniques, optimized memory management for large datasets, or machine learning integration to better address diverse application requirements.