Image Preprocessing: Normalization, Edge Detection, and Related MATLAB Code Implementations

This document presents several compact MATLAB programs designed for image preprocessing operations such as normalization and edge detection. These implementations incorporate diverse algorithms and processing techniques to handle digital images effectively. Image preprocessing normalization serves as a fundamental technique to standardize pixel value ranges, typically through min-max scaling or z-score normalization methods, which significantly improves processing accuracy and computational efficiency. Edge detection algorithms, including Sobel, Prewitt, or Canny operators implemented using convolution kernels, help identify object boundaries and contours within images by detecting intensity gradients. The code samples demonstrate practical applications of these techniques using MATLAB's Image Processing Toolbox functions like imadjust for normalization and edge function with different method parameters for boundary detection. These programs are structured to provide immediate utility for research and educational purposes, featuring commented code sections explaining key algorithmic steps. Should you have any technical inquiries or improvement suggestions regarding the implementations, please feel free to contact me for further discussion.