Wavelet Transform-Based Edge Detection with MATLAB Implementation

This MATLAB program implements edge detection based on wavelet transform. Edge detection is a fundamental technique in image processing used to identify object boundaries within images. Wavelet transform serves as a mathematical tool for signal analysis and processing, particularly effective for multi-resolution analysis. The program follows a structured workflow: 1. Image Reading: Utilizes MATLAB's imread() function to load input images 2. Wavelet Decomposition: Implements discrete wavelet transform (DWT) using functions like wavedec2() for 2D signal decomposition 3. Coefficient Processing: Applies thresholding techniques to wavelet coefficients to enhance edge information 4. Inverse Transform: Reconstructs the edge-enhanced image using waverec2() function Key algorithmic features include: - Multi-scale edge detection through different wavelet decomposition levels - Adjustable threshold parameters for sensitivity control - Support for various wavelet families (Haar, Daubechies, etc.) - Noise reduction capabilities through coefficient thresholding The program allows researchers and developers to obtain edge detection results with varying precision and effects by modifying parameters and algorithms. It serves as a practical tool for edge detection-related work in image processing applications, offering insights into wavelet-based feature extraction methodologies.