Multiscale Image Edge Detection Based on Wavelet Transform

This MATLAB-implemented program utilizes wavelet transform for multiscale image edge detection. Wavelet transform serves as a mathematical tool that decomposes images into frequency components across different scales, effectively revealing detailed features and edge characteristics. The implementation employs discrete wavelet transform (DWT) functions like wavedec2 for multilevel decomposition and edge extraction through detailed coefficient analysis at various resolution levels. Key algorithmic steps include: 1) Applying wavelet decomposition using db4 or similar wavelets 2) Processing horizontal, vertical and diagonal detail coefficients 3) Implementing multi-threshold edge reconstruction from wavelet coefficients. The MATLAB environment enables flexible parameter adjustments through functions such as wthresh for coefficient thresholding and edge enhancement techniques. This design leverages MATLAB's computational efficiency and graphical capabilities for optimizing edge detection performance across multiple scales while maintaining precise control over decomposition levels and threshold parameters.