Xiaohua Xia , Dianbin Yang , Shaobo Huo , Jianhong Sun , Huatao Xiang
{"title":"基于光流跟踪和 Delaunay 三角测量的多焦点图像配准","authors":"Xiaohua Xia , Dianbin Yang , Shaobo Huo , Jianhong Sun , Huatao Xiang","doi":"10.1016/j.sigpro.2024.109763","DOIUrl":null,"url":null,"abstract":"<div><div>In the fields of multi-focus image fusion and shape from focus, accurate registration of multi-focus images is a crucial prerequisite. Due to the difficulty of feature detection in defocused regions and the limitations of global registration methods, traditional multi-focus image registration methods have low accuracy. To solve this problem, a novel multi-focus image registration method based on optical flow tracking and Delaunay triangulation is proposed. The innovation includes two aspects. The first is that optical flow tracking is utilized to extract and match the non-salient features of multi-focus images. It greatly increases the number of matching features in the defocused regions of multi-focus images. The second is that Delaunay triangulation is adopted for local registration. It makes the matching features strictly aligned. The results of the experiments show that the proposed method is superior to the traditional methods in terms of image registration accuracy and image fusion quality.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109763"},"PeriodicalIF":3.4000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-focus image registration based on optical flow tracking and Delaunay triangulation\",\"authors\":\"Xiaohua Xia , Dianbin Yang , Shaobo Huo , Jianhong Sun , Huatao Xiang\",\"doi\":\"10.1016/j.sigpro.2024.109763\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In the fields of multi-focus image fusion and shape from focus, accurate registration of multi-focus images is a crucial prerequisite. Due to the difficulty of feature detection in defocused regions and the limitations of global registration methods, traditional multi-focus image registration methods have low accuracy. To solve this problem, a novel multi-focus image registration method based on optical flow tracking and Delaunay triangulation is proposed. The innovation includes two aspects. The first is that optical flow tracking is utilized to extract and match the non-salient features of multi-focus images. It greatly increases the number of matching features in the defocused regions of multi-focus images. The second is that Delaunay triangulation is adopted for local registration. It makes the matching features strictly aligned. The results of the experiments show that the proposed method is superior to the traditional methods in terms of image registration accuracy and image fusion quality.</div></div>\",\"PeriodicalId\":49523,\"journal\":{\"name\":\"Signal Processing\",\"volume\":\"228 \",\"pages\":\"Article 109763\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0165168424003839\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168424003839","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Multi-focus image registration based on optical flow tracking and Delaunay triangulation
In the fields of multi-focus image fusion and shape from focus, accurate registration of multi-focus images is a crucial prerequisite. Due to the difficulty of feature detection in defocused regions and the limitations of global registration methods, traditional multi-focus image registration methods have low accuracy. To solve this problem, a novel multi-focus image registration method based on optical flow tracking and Delaunay triangulation is proposed. The innovation includes two aspects. The first is that optical flow tracking is utilized to extract and match the non-salient features of multi-focus images. It greatly increases the number of matching features in the defocused regions of multi-focus images. The second is that Delaunay triangulation is adopted for local registration. It makes the matching features strictly aligned. The results of the experiments show that the proposed method is superior to the traditional methods in terms of image registration accuracy and image fusion quality.
期刊介绍:
Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing.
Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.