MATLAB Code Implementation for Common Image Processing

This resource offers practical MATLAB source code samples for common image processing tasks. The provided implementations cover essential techniques such as color inversion (converting pixel values via 255-value subtraction), various filtering algorithms (including mean, median, and Gaussian filters for smoothing and edge detection), noise removal methods (using wavelet transforms or adaptive filtering), and standard image transformations (Fourier Transform, DCT, and geometric transformations). These code samples demonstrate how to process images and achieve various effects through different algorithmic approaches. Whether you need to adjust image coloration or enhance image details, these implementations provide working solutions with comments explaining key functions like imread(), imfilter(), and fft2(). The code includes practical examples of histogram equalization, thresholding operations, and spatial domain filtering techniques. We hope these well-documented code examples serve as valuable references for your image processing projects.