Quantum image edge detection based on Haar wavelet transform
Quantum edge detection offers a promising avenue for real-time image analysis, addressing constraints faced by classical algorithms. However, existing quantum edge detection methods often rely on classical edge detection operators, leading to the loss of intricate edge details, especially in high-re...
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| Veröffentlicht in: | Quantum information processing 2024-08, Vol.23 (8), Article 302 |
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| container_title | Quantum information processing |
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| creator | Wang, Guoling Zhao, Weiqian Zou, Ping Wang, Jindong Yin, Haibing Yu, Yafei |
| description | Quantum edge detection offers a promising avenue for real-time image analysis, addressing constraints faced by classical algorithms. However, existing quantum edge detection methods often rely on classical edge detection operators, leading to the loss of intricate edge details, especially in high-resolution images. Here, we present a novel quantum image edge detection algorithm. Our approach involves transforming the image into the wavelet domain through wavelet transform, performing edge detection, and obtaining the edge image via inverse wavelet transform. This innovative method not only mitigates edge information loss but also enhances precision in delineation. Through comprehensive simulations on a classical computing platform, employing peak signal-to-noise ratio (PSNR) and Edge Preservation Index (EPI) evaluations, our proposed scheme demonstrates superior edge information and heightened accuracy. These results underscore the potential of our approach in advancing image processing techniques. |
| doi_str_mv | 10.1007/s11128-024-04513-8 |
| format | Article |
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| subjects | Algorithms Data Structures and Information Theory Edge detection Image analysis Image processing Image resolution Mathematical Physics Physics Physics and Astronomy Quantum Computing Quantum Information Technology Quantum Physics Real time Signal to noise ratio Spintronics Wavelet analysis Wavelet transforms |
| title | Quantum image edge detection based on Haar wavelet transform |
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