{"title":"多层次交叉视点线匹配:利用空间域特征。","authors":"Jiaxuan Song, Yang Dong, Dazhao Fan, Song Ji","doi":"10.1364/JOSAA.606270","DOIUrl":null,"url":null,"abstract":"<p><p>Cross-view line matching is critical for high-resolution urban modeling, but existing methods rely on priors and struggle with curves. Thus, we propose a multi-level cross-view line matching method by spatial domain characteristics. It employs fast affine simulation to compensate for distortion and introduces the perspective invariance of coplanar line intersections to obtain multi-type corresponding line pairs and line features. Then, local homography constraints are established to achieve single-line grouping and matching. Experiments demonstrate that our method outperforms baselines in matching accuracy and efficiency, and supports curve matching, providing an efficient approach for reconstruction based on irregular contours.</p>","PeriodicalId":17382,"journal":{"name":"Journal of The Optical Society of America A-optics Image Science and Vision","volume":"43 10","pages":"1624-1637"},"PeriodicalIF":1.5000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-level cross-view line matching: exploiting spatial domain characteristics.\",\"authors\":\"Jiaxuan Song, Yang Dong, Dazhao Fan, Song Ji\",\"doi\":\"10.1364/JOSAA.606270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cross-view line matching is critical for high-resolution urban modeling, but existing methods rely on priors and struggle with curves. Thus, we propose a multi-level cross-view line matching method by spatial domain characteristics. It employs fast affine simulation to compensate for distortion and introduces the perspective invariance of coplanar line intersections to obtain multi-type corresponding line pairs and line features. Then, local homography constraints are established to achieve single-line grouping and matching. Experiments demonstrate that our method outperforms baselines in matching accuracy and efficiency, and supports curve matching, providing an efficient approach for reconstruction based on irregular contours.</p>\",\"PeriodicalId\":17382,\"journal\":{\"name\":\"Journal of The Optical Society of America A-optics Image Science and Vision\",\"volume\":\"43 10\",\"pages\":\"1624-1637\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2026-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of The Optical Society of America A-optics Image Science and Vision\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1364/JOSAA.606270\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of The Optical Society of America A-optics Image Science and Vision","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1364/JOSAA.606270","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPTICS","Score":null,"Total":0}
Multi-level cross-view line matching: exploiting spatial domain characteristics.
Cross-view line matching is critical for high-resolution urban modeling, but existing methods rely on priors and struggle with curves. Thus, we propose a multi-level cross-view line matching method by spatial domain characteristics. It employs fast affine simulation to compensate for distortion and introduces the perspective invariance of coplanar line intersections to obtain multi-type corresponding line pairs and line features. Then, local homography constraints are established to achieve single-line grouping and matching. Experiments demonstrate that our method outperforms baselines in matching accuracy and efficiency, and supports curve matching, providing an efficient approach for reconstruction based on irregular contours.
期刊介绍:
The Journal of the Optical Society of America A (JOSA A) is devoted to developments in any field of classical optics, image science, and vision. JOSA A includes original peer-reviewed papers on such topics as:
* Atmospheric optics
* Clinical vision
* Coherence and Statistical Optics
* Color
* Diffraction and gratings
* Image processing
* Machine vision
* Physiological optics
* Polarization
* Scattering
* Signal processing
* Thin films
* Visual optics
Also: j opt soc am a.