A New Local Optimal Spline Wavelet for Image Edge Detection
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| Publicado en: | Mathematics vol. 13, no. 1 (2025), p. 42 |
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| Otros Autores: | , , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2227-7390 | ||
| 024 | 7 | |a 10.3390/math13010042 |2 doi | |
| 035 | |a 3153800413 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231533 |2 nlm | ||
| 100 | 1 | |a Zhou, Dujuan |u School of Computer Science and Engineering, Macau University of Science and Technology, Taipa, Macau, China; <email>2202853gii30002@student.must.edu.mo</email>; School of Mathematics, Physics and Civil Engineering, Beijing Institute of Technology, Zhuhai 519088, China; <email>210110101171@bitzh.edu.cn</email> | |
| 245 | 1 | |a A New Local Optimal Spline Wavelet for Image Edge Detection | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Computational mathematics | ||
| 653 | |a Monte Carlo simulation | ||
| 653 | |a Accuracy | ||
| 653 | |a Wavelet transforms | ||
| 653 | |a Image reconstruction | ||
| 653 | |a Fourier transforms | ||
| 653 | |a Image filters | ||
| 653 | |a Noise reduction | ||
| 653 | |a Neural networks | ||
| 653 | |a Signal processing | ||
| 653 | |a Fractals | ||
| 653 | |a Algorithms | ||
| 653 | |a Computer vision | ||
| 653 | |a Methods | ||
| 653 | |a Localization | ||
| 653 | |a Image processing | ||
| 653 | |a Pattern recognition | ||
| 653 | |a Morphology | ||
| 653 | |a Edge detection | ||
| 700 | 1 | |a Yuan, Zizhao |u School of Mathematics, Physics and Civil Engineering, Beijing Institute of Technology, Zhuhai 519088, China; <email>210110101171@bitzh.edu.cn</email> | |
| 700 | 1 | |a Cai, Zhanchuan |u School of Computer Science and Engineering, Macau University of Science and Technology, Taipa, Macau, China; <email>2202853gii30002@student.must.edu.mo</email> | |
| 700 | 1 | |a Zhu, Defu |u Key Laboratory of In-Situ Property-Improving Mining of Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China; <email>zhudefu@tyut.edu.cn</email>; Galuminium Group Co., Ltd., Guangzhou 510450, China | |
| 700 | 1 | |a Shen, Xiaojing |u Faculty of Data Science, City University of Macau, Macau, China; <email>d23092100546@cityu.edu.mo</email> | |
| 773 | 0 | |t Mathematics |g vol. 13, no. 1 (2025), p. 42 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3153800413/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3153800413/fulltextwithgraphics/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3153800413/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |