Wavelet Transform for Image Enhancement with MATLAB Source Code

This article explores the application of wavelet transform for image enhancement. Wavelet transform is a mathematical tool that decomposes signals or images into frequency components at different scales. By performing wavelet decomposition on an image, we can extract detailed texture information and enhance image clarity and contrast. The implementation involves key steps: first applying discrete wavelet transform (DWT) using functions like wavedec2 to decompose the image into approximation and detail coefficients (horizontal, vertical, diagonal). Then, enhancement is achieved by strategically modifying these coefficients - typically amplifying high-frequency components while preserving low-frequency structures. We provide complete MATLAB source code demonstrating practical implementation, including coefficient thresholding techniques and reconstruction using waverec2. Through this guide, readers will gain understanding of wavelet-based image processing and hands-on experience with MATLAB implementation for enhancing image quality through multi-scale analysis.