MATLAB Implementation of Wavelet Transform for Edge Detection

This paper presents an image edge detection algorithm utilizing wavelet transform and edge fusion techniques. The algorithm performs layered detection, decomposition, and reconstruction of images across multiple scales, enabling more precise capture of edge details and enhanced image processing effectiveness. Specifically, the implementation begins with wavelet transform preprocessing of the input image using MATLAB's wavelet toolbox functions (e.g., wavedec2 for 2D decomposition). The edge fusion algorithm then integrates edge information from different scales through weighted combination methods implemented via custom fusion functions. Finally, the reconstruction algorithm employs inverse wavelet transforms (waverec2) to restore the fused edge information back to the original image. This multi-scale approach yields clearer and more accurate edge detection results, providing a more reliable foundation for subsequent image analysis and processing tasks. The code structure typically involves wavelet decomposition at multiple levels, edge magnitude calculation at each scale, fusion rule implementation, and progressive reconstruction operations.