MATLAB Code Implementation for Image Processing

MATLAB serves as a powerful image processing tool capable of performing various image smoothing and sharpening operations. Image smoothing can be achieved through methods like mean filtering and median filtering. Mean filtering typically uses the imfilter() function with averaging kernels to reduce noise by replacing each pixel with the average of its neighborhood. Median filtering, implemented via medfilt2(), effectively removes salt-and-pepper noise by replacing pixel values with the median of surrounding pixels while preserving edges better than linear filters. Image sharpening enhances edges and details using operators such as Laplacian, Roberts, Prewitt, and Sobel. The Laplacian operator, implemented through fspecial('laplacian') and imfilter(), highlights regions of rapid intensity change. Edge detection operators like Roberts (edge(I,'roberts')), Prewitt (edge(I,'prewitt')), and Sobel (edge(I,'sobel')) calculate gradients to emphasize boundaries. These operators work by convolving specific kernels with the image to detect horizontal and vertical edges. By employing these image processing techniques with appropriate MATLAB functions, images can be made more visually appealing, accurate, and attractive through effective noise reduction and edge enhancement.