MATLAB Implementation of Digital Image Processing Techniques

In the field of digital image processing, numerous important techniques and algorithms can be implemented using MATLAB. One fundamental method is the Fourier Transform, which converts images from the spatial domain to the frequency domain using MATLAB's fft2() function, providing enhanced frequency information for analysis. Another widely used technique is Wavelet Transform, implemented through functions like wavedec2() for multi-scale analysis of image details and features at different resolution levels. Additionally, sharpening algorithms serve as common image enhancement methods, where MATLAB's fspecial() function with 'unsharp' or 'laplacian' filters can significantly improve image clarity and detail visibility. Histogram equalization techniques, achievable through histeq() or adapthisteq() functions, effectively enhance image contrast and optimize brightness distribution. These MATLAB-implemented techniques and algorithms provide a rich toolkit for digital image processing, enabling more effective image manipulation and quality improvement through practical code implementation approaches.