MATLAB Implementation of Image Processing Algorithms

In this article, we delve deeper into MATLAB-based image processing algorithms implemented through six distinct program codes. These implementations serve as excellent educational resources for image processing studies. The algorithms demonstrate practical approaches to various image manipulation techniques, including brightness adjustment using imadjust() function, contrast enhancement through histogram equalization with histeq(), and application of different filters like medfilt2() for noise reduction. Additionally, the codes cover edge detection methods employing operators such as Sobel and Canny, feature extraction techniques using regionprops() function, and image segmentation approaches including watershed algorithm. These MATLAB implementations provide hands-on experience in understanding how to process digital images effectively, making them valuable for enhancing knowledge and skills in the image processing domain. The commented code structure helps learners understand algorithm flow and MATLAB's image processing toolbox capabilities.