MATLAB Code for Image Processing Operations

This MATLAB code collection provides comprehensive implementations for various image processing operations. Point operations involve pixel-level transformations using functions like imadjust for linear operations and im2uint8 for nonlinear mapping. Arithmetic operations utilize imadd, imsubtract, immultiply, and imdivide functions for basic mathematical operations between images. Bitwise operations employ bitand, bitor, and bitxor functions for logical image manipulations. Geometric operations include imresize with interpolation methods ('nearest', 'bilinear', 'bicubic') for scaling, imrotate for image rotation, and imcrop for cropping operations. Spatial transformations implement affine transforms using affine2d and imwarp functions, while perspective transformations use projective2d for more complex spatial manipulations. Image fusion techniques combine multiple images using weighted averaging or pyramid-based methods. Neighborhood operations process images using sliding window techniques with nlfilter, while block operations utilize blockproc for partitioned image processing. Region processing includes region selection via roipoly, region filtering using morphological operations, and region filling with imfill. Image enhancement employs histeq for histogram equalization and adapthisteq for adaptive contrast enhancement. Segmentation techniques implement thresholding using graythresh and imbinarize, edge detection with edge function (Sobel, Canny), and region-based methods through watershed or region growing algorithms. Denoising implementations include linear filters (imfilter with predefined kernels), nonlinear filters (medfilt2 for median filtering), statistical filters, and adaptive filters that adjust parameters based on local image characteristics. Compression algorithms cover lossless methods (Huffman coding, LZW) and lossy techniques (JPEG, wavelet compression) using various quantization and encoding strategies.