Yeyang Jiang, Li Zhu, Xing Liu, Cunrong Song, Xi Yang
{"title":"基于复变分析法的图像重建算法研究","authors":"Yeyang Jiang, Li Zhu, Xing Liu, Cunrong Song, Xi Yang","doi":"10.1109/ICMTMA50254.2020.00135","DOIUrl":null,"url":null,"abstract":"In order to improve the recognition ability of fuzzy sparse scattered feature distribution image, it is necessary to carry out spatial vision distributed reconstruction and image virtual reconstruction. A virtual reconstruction method of sparse scattered feature distribution image based on complex analysis method is proposed. The grid distribution model of sparse scattered feature distribution image is constructed, and the spatial information feature distributed reconstruction model of sparse scattered feature distribution image is carried out by using image sparse feature point extraction method. Combined with block feature detection and image segmentation method, the boundary region detection of sparse scattered feature distribution image is carried out, and the spatial visual distributed reconstruction model of sparse scattered feature distribution image is established. Combined with fuzzy structure reconstruction method, the image filtering and information fusion of sparse scattered feature distribution image are carried out. according to the texture and detail area of sparse scattered feature distribution image, the 3D texture structure and sparse evacuation scrambling point reconstruction of image are carried out, and the 3D reconstruction of image is carried out by complex analysis method, and the gray histogram of sparse scattered feature distribution image is reconstructed. Virtual reconstruction of sparse scattered feature distribution image is realized based on spatial vision distributed reconstruction. The simulation results show that the visual effect of virtual reconstruction of sparse scattered feature distribution image is better, and the quality of 3D image virtual reconstruction is higher.","PeriodicalId":333866,"journal":{"name":"2020 12th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Image Reconstruction Algorithm Based on Complex Analysis Method\",\"authors\":\"Yeyang Jiang, Li Zhu, Xing Liu, Cunrong Song, Xi Yang\",\"doi\":\"10.1109/ICMTMA50254.2020.00135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the recognition ability of fuzzy sparse scattered feature distribution image, it is necessary to carry out spatial vision distributed reconstruction and image virtual reconstruction. A virtual reconstruction method of sparse scattered feature distribution image based on complex analysis method is proposed. The grid distribution model of sparse scattered feature distribution image is constructed, and the spatial information feature distributed reconstruction model of sparse scattered feature distribution image is carried out by using image sparse feature point extraction method. Combined with block feature detection and image segmentation method, the boundary region detection of sparse scattered feature distribution image is carried out, and the spatial visual distributed reconstruction model of sparse scattered feature distribution image is established. Combined with fuzzy structure reconstruction method, the image filtering and information fusion of sparse scattered feature distribution image are carried out. according to the texture and detail area of sparse scattered feature distribution image, the 3D texture structure and sparse evacuation scrambling point reconstruction of image are carried out, and the 3D reconstruction of image is carried out by complex analysis method, and the gray histogram of sparse scattered feature distribution image is reconstructed. Virtual reconstruction of sparse scattered feature distribution image is realized based on spatial vision distributed reconstruction. The simulation results show that the visual effect of virtual reconstruction of sparse scattered feature distribution image is better, and the quality of 3D image virtual reconstruction is higher.\",\"PeriodicalId\":333866,\"journal\":{\"name\":\"2020 12th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 12th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMTMA50254.2020.00135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 12th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMTMA50254.2020.00135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Image Reconstruction Algorithm Based on Complex Analysis Method
In order to improve the recognition ability of fuzzy sparse scattered feature distribution image, it is necessary to carry out spatial vision distributed reconstruction and image virtual reconstruction. A virtual reconstruction method of sparse scattered feature distribution image based on complex analysis method is proposed. The grid distribution model of sparse scattered feature distribution image is constructed, and the spatial information feature distributed reconstruction model of sparse scattered feature distribution image is carried out by using image sparse feature point extraction method. Combined with block feature detection and image segmentation method, the boundary region detection of sparse scattered feature distribution image is carried out, and the spatial visual distributed reconstruction model of sparse scattered feature distribution image is established. Combined with fuzzy structure reconstruction method, the image filtering and information fusion of sparse scattered feature distribution image are carried out. according to the texture and detail area of sparse scattered feature distribution image, the 3D texture structure and sparse evacuation scrambling point reconstruction of image are carried out, and the 3D reconstruction of image is carried out by complex analysis method, and the gray histogram of sparse scattered feature distribution image is reconstructed. Virtual reconstruction of sparse scattered feature distribution image is realized based on spatial vision distributed reconstruction. The simulation results show that the visual effect of virtual reconstruction of sparse scattered feature distribution image is better, and the quality of 3D image virtual reconstruction is higher.