MATLAB Implementation of Compiled Wavelet Transform for Image Fusion and Processing

I will implement a wavelet transform algorithm using MATLAB, designed for image fusion and processing of image files within folders. Wavelet transform is a fundamental mathematical tool widely used in signal processing and image analysis, capable of decomposing signals or images into multiple frequency components while providing enhanced detail resolution and precision. The implementation involves using MATLAB's Wavelet Toolbox functions such as wavedec2 for 2D wavelet decomposition and waverec2 for reconstruction. For image fusion, we'll employ a multi-resolution approach where we decompose source images using discrete wavelet transform (DWT), apply fusion rules to approximation and detail coefficients, then reconstruct the fused image. The algorithm will include coefficient selection methods like maximum selection or weighted average for different frequency bands. For folder-based image processing, the code will implement batch processing capabilities using dir function to scan directories, followed by wavelet-based operations including: - Denoising using thresholding techniques (soft/hard thresholding) on detail coefficients - Edge detection through gradient analysis of high-frequency components - Filtering by modifying specific frequency bands in the wavelet domain The implementation will feature a main processing loop that automatically handles multiple image formats, applies wavelet transforms with configurable parameters (wavelet type, decomposition level), and saves processed images in specified output directories. This approach transforms folder images into usable fused images that combine information from multiple sources while enhancing visual quality and extracting relevant features for various application requirements.