{"title":"基于哈尔小波变换的量子图像边缘检测","authors":"Guoling Wang, Weiqian Zhao, Ping Zou, Jindong Wang, Haibing Yin, Yafei Yu","doi":"10.1007/s11128-024-04513-8","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":746,"journal":{"name":"Quantum Information Processing","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantum image edge detection based on Haar wavelet transform\",\"authors\":\"Guoling Wang, Weiqian Zhao, Ping Zou, Jindong Wang, Haibing Yin, Yafei Yu\",\"doi\":\"10.1007/s11128-024-04513-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":746,\"journal\":{\"name\":\"Quantum Information Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quantum Information Processing\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11128-024-04513-8\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSICS, MATHEMATICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantum Information Processing","FirstCategoryId":"101","ListUrlMain":"https://link.springer.com/article/10.1007/s11128-024-04513-8","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, MATHEMATICAL","Score":null,"Total":0}
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-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.
期刊介绍:
Quantum Information Processing is a high-impact, international journal publishing cutting-edge experimental and theoretical research in all areas of Quantum Information Science. Topics of interest include quantum cryptography and communications, entanglement and discord, quantum algorithms, quantum error correction and fault tolerance, quantum computer science, quantum imaging and sensing, and experimental platforms for quantum information. Quantum Information Processing supports and inspires research by providing a comprehensive peer review process, and broadcasting high quality results in a range of formats. These include original papers, letters, broadly focused perspectives, comprehensive review articles, book reviews, and special topical issues. The journal is particularly interested in papers detailing and demonstrating quantum information protocols for cryptography, communications, computation, and sensing.