{"title":"量子图像处理二十年的经验教训","authors":"Fei Yan, S. Venegas-Andraca","doi":"10.1145/3663577","DOIUrl":null,"url":null,"abstract":"Quantum image processing (QIMP) was first introduced in 2003, by Venegas-Andraca et al. at the University of Oxford. This field attempts to overcome the limitations of classical computers and the potentially overwhelming complexity of classical algorithms by providing a more effective way to store and manipulate visual information. Over the past 20 years, QIMP has become an active area of research, experiencing rapid and vigorous development. However, these advancements have suffered from an imbalance, as inherent critical issues have been largely ignored. In this paper, we review the original intentions for this field and analyze various unresolved issues from a new perspective, including QIMP algorithm design, potential advantages and limitations, technological debates, and potential directions for future development. We suggest the 20-year milestone could serve as a new beginning and advocate for more researchers to focus their attention on this pursuit, helping to overcome bottlenecks, and achieving more practical results in the future.","PeriodicalId":474832,"journal":{"name":"ACM transactions on quantum computing","volume":"29 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lessons from Twenty Years of Quantum Image Processing\",\"authors\":\"Fei Yan, S. Venegas-Andraca\",\"doi\":\"10.1145/3663577\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantum image processing (QIMP) was first introduced in 2003, by Venegas-Andraca et al. at the University of Oxford. This field attempts to overcome the limitations of classical computers and the potentially overwhelming complexity of classical algorithms by providing a more effective way to store and manipulate visual information. Over the past 20 years, QIMP has become an active area of research, experiencing rapid and vigorous development. However, these advancements have suffered from an imbalance, as inherent critical issues have been largely ignored. In this paper, we review the original intentions for this field and analyze various unresolved issues from a new perspective, including QIMP algorithm design, potential advantages and limitations, technological debates, and potential directions for future development. We suggest the 20-year milestone could serve as a new beginning and advocate for more researchers to focus their attention on this pursuit, helping to overcome bottlenecks, and achieving more practical results in the future.\",\"PeriodicalId\":474832,\"journal\":{\"name\":\"ACM transactions on quantum computing\",\"volume\":\"29 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM transactions on quantum computing\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.1145/3663577\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM transactions on quantum computing","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1145/3663577","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lessons from Twenty Years of Quantum Image Processing
Quantum image processing (QIMP) was first introduced in 2003, by Venegas-Andraca et al. at the University of Oxford. This field attempts to overcome the limitations of classical computers and the potentially overwhelming complexity of classical algorithms by providing a more effective way to store and manipulate visual information. Over the past 20 years, QIMP has become an active area of research, experiencing rapid and vigorous development. However, these advancements have suffered from an imbalance, as inherent critical issues have been largely ignored. In this paper, we review the original intentions for this field and analyze various unresolved issues from a new perspective, including QIMP algorithm design, potential advantages and limitations, technological debates, and potential directions for future development. We suggest the 20-year milestone could serve as a new beginning and advocate for more researchers to focus their attention on this pursuit, helping to overcome bottlenecks, and achieving more practical results in the future.