MATLAB Function for Image Denoising Using Wavelet Transform

This MATLAB function performs image denoising using wavelet transform, a common image processing technique that enhances image quality and clarity. Wavelet transform is a mathematical tool that decomposes signals or images into sub-signals or sub-images at different frequency components. By processing these components, we can effectively remove noise while preserving essential image details. The function implements a standard denoising workflow: decomposing the input image using wavelet functions like 'db4' or 'sym8', applying thresholding techniques (soft or hard thresholding) to wavelet coefficients to suppress noise, and reconstructing the denoised image through inverse wavelet transform. Key parameters include wavelet type selection, threshold determination methods (universal threshold or SURE threshold), and decomposition level control, allowing users to customize denoising intensity and results according to specific requirements. This implementation typically utilizes MATLAB's Wavelet Toolbox functions such as wavedec2 for decomposition and waverec2 for reconstruction. We hope this function proves valuable for your image processing tasks!