Content area
Wavelet-based edge detection methods have evolved significantly over the years, contributing to advances in image processing, computer vision, and pattern recognition. This paper proposes a new local optimal spline wavelet (LOSW) and the dual wavelet of the LOSW. Then, a pair of dual filters can be obtained, which can provide distortion-free signal decomposition and reconstruction, while having stronger denoising and feature capture capabilities. The coefficients of the pair of dual filters are calculated for image edge detection. We propose a new LOSW-based edge detection algorithm (LOSW-ED), which introduces a structural uncertainty–aware modulus maxima (SUAMM) to detect highly uncertain edge samples, ensuring robustness in complex and noisy environments. Additionally, LOSW-ED unifies multi-structure morphology and modulus maxima to fully exploit the complementary properties of low-frequency (LF) and high-frequency (HF) components, enabling multi-stage differential edge refinement. The experimental results show that the proposed LOSW and LOSW-ED algorithm has better performance in noise suppression and edge structure preservation.
Details
Monte Carlo simulation;
Accuracy;
Wavelet transforms;
Image reconstruction;
Fourier transforms;
Image filters;
Noise reduction;
Neural networks;
Signal processing;
Fractals;
Algorithms;
Computer vision;
Methods;
Localization;
Image processing;
Pattern recognition;
Morphology;
Edge detection
; Yuan, Zizhao 2
; Cai, Zhanchuan 3
; Zhu, Defu 4
; Shen, Xiaojing 5
1 School of Computer Science and Engineering, Macau University of Science and Technology, Taipa, Macau, China;
2 School of Mathematics, Physics and Civil Engineering, Beijing Institute of Technology, Zhuhai 519088, China;
3 School of Computer Science and Engineering, Macau University of Science and Technology, Taipa, Macau, China;
4 Key Laboratory of In-Situ Property-Improving Mining of Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China;
5 Faculty of Data Science, City University of Macau, Macau, China;