MATLAB Implementation of Wavelet Transform Applications

This MATLAB program implements wavelet transform-based applications, providing multiple image processing functionalities for operations such as image enhancement, image decomposition, image denoising, and image fusion. The image enhancement module utilizes wavelet coefficient modification to improve image clarity and contrast, making images more vivid through techniques like histogram equalization and contrast stretching. The image decomposition feature employs multi-scale wavelet decomposition (using functions like wavedec2) to break down original images into different frequency bands, enabling detailed analysis and processing of image components at various scales. The denoising functionality implements thresholding algorithms (such as VisuShrink or BayesShrink) on wavelet coefficients to eliminate noise points and interference, significantly improving image quality while preserving important features. The image fusion capability combines images from different sources using wavelet coefficient fusion rules (like maximum selection or weighted average) to generate new composite images, facilitating comprehensive data analysis and processing. The program is user-friendly with clear function interfaces and parameter configurations, allowing users to efficiently process image data through simple function calls and customizable wavelet parameters (wavelet type, decomposition levels).