Multi-scale Image Edge Detection Based on Wavelet Transform Modulus Maxima

This article presents MATLAB source code for multi-scale image edge detection based on wavelet transform modulus maxima. We begin by explaining the fundamental principles of wavelet transform and its applications in image processing. The algorithm employs multi-scale analysis through wavelet decomposition, where edge points are identified by tracking modulus maxima across different scales. Key implementation steps include: performing 2D discrete wavelet transform using functions like wavedec2, calculating gradient magnitudes and directions, detecting modulus maxima points that represent significant intensity variations, and applying multi-scale fusion to combine edge information from different resolution levels. We provide complete MATLAB code examples demonstrating how to implement the modulus maxima detection algorithm using wavelet toolbox functions, including proper thresholding techniques to reduce noise while preserving true edges. The code implementation covers critical aspects such as scale selection, edge linking, and results visualization using MATLAB's image processing capabilities. Finally, we discuss the method's advantages in handling noise robustness and scale adaptability, while addressing limitations in computational complexity and parameter sensitivity. Potential improvements including adaptive thresholding and combining with other edge detection methods are explored. Through this comprehensive guide, readers will gain deep understanding of wavelet-based modulus maxima edge detection and achieve better results in practical applications.