Image Sharpening: Sobel Operator-Based Enhancement Algorithm

The Sobel operator-based image sharpening enhancement algorithm can be implemented through the following systematic steps. First, preprocess the input image by converting it to grayscale using standard color-to-gray conversion techniques (typically weighted average: 0.299*R + 0.587*G + 0.114*B). Next, apply the Sobel operator for edge detection by convolving the grayscale image with horizontal and vertical derivative kernels (Gx = [[-1,0,1],[-2,0,2],[-1,0,1]], Gy = [[-1,-2,-1],[0,0,0],[1,2,1]]) to compute gradient magnitude. Then, employ a sharpening filter (commonly unsharp masking or high-boost filtering) to enhance edge details by amplifying high-frequency components while preserving low-frequency information. Finally, blend the sharpened edge image with the original image using weighted addition or alpha blending techniques to produce the final enhanced output. This method effectively improves visual quality by emphasizing structural details and increasing perceived sharpness through controlled edge enhancement.