{"title":"面向数字地形模型生成的高精度图像匹配","authors":"Armin W. Gruen, Emmanuel P. Baltsavias","doi":"10.1016/0031-8663(87)90045-7","DOIUrl":null,"url":null,"abstract":"<div><p>The Adaptive Least Squares Correlation (ALSC), combining gray-level correlation with geometric conditions, was applied to a grid-sampling mode for generation of Digital Terrain Models (DTM) from aerial stereo models.</p><p>The heights of targets of different geometric and contrast quality in large-scale digitized images were determined using this technique and compared to results from manual measurements. Both solutions showed an average difference of 0.016–0.038% and a maximum differences of 0.037–0.120% flying height (hg), depending on the height approximation. Most cases investigated required an initial height approximation at the 1–2% hg level. An average height error of 0.2% hg was cleared in each iteration step. The constraints imposed proved to define the movement of the gray-level image patches, thus limiting the search area and probability of false correlation, and increasing the precision and reliability of height determination.</p></div>","PeriodicalId":101020,"journal":{"name":"Photogrammetria","volume":"42 3","pages":"Pages 97-112"},"PeriodicalIF":0.0000,"publicationDate":"1987-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0031-8663(87)90045-7","citationCount":"75","resultStr":"{\"title\":\"High-precision image matching for digital terrain model generation\",\"authors\":\"Armin W. Gruen, Emmanuel P. Baltsavias\",\"doi\":\"10.1016/0031-8663(87)90045-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The Adaptive Least Squares Correlation (ALSC), combining gray-level correlation with geometric conditions, was applied to a grid-sampling mode for generation of Digital Terrain Models (DTM) from aerial stereo models.</p><p>The heights of targets of different geometric and contrast quality in large-scale digitized images were determined using this technique and compared to results from manual measurements. Both solutions showed an average difference of 0.016–0.038% and a maximum differences of 0.037–0.120% flying height (hg), depending on the height approximation. Most cases investigated required an initial height approximation at the 1–2% hg level. An average height error of 0.2% hg was cleared in each iteration step. The constraints imposed proved to define the movement of the gray-level image patches, thus limiting the search area and probability of false correlation, and increasing the precision and reliability of height determination.</p></div>\",\"PeriodicalId\":101020,\"journal\":{\"name\":\"Photogrammetria\",\"volume\":\"42 3\",\"pages\":\"Pages 97-112\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0031-8663(87)90045-7\",\"citationCount\":\"75\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Photogrammetria\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0031866387900457\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photogrammetria","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0031866387900457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High-precision image matching for digital terrain model generation
The Adaptive Least Squares Correlation (ALSC), combining gray-level correlation with geometric conditions, was applied to a grid-sampling mode for generation of Digital Terrain Models (DTM) from aerial stereo models.
The heights of targets of different geometric and contrast quality in large-scale digitized images were determined using this technique and compared to results from manual measurements. Both solutions showed an average difference of 0.016–0.038% and a maximum differences of 0.037–0.120% flying height (hg), depending on the height approximation. Most cases investigated required an initial height approximation at the 1–2% hg level. An average height error of 0.2% hg was cleared in each iteration step. The constraints imposed proved to define the movement of the gray-level image patches, thus limiting the search area and probability of false correlation, and increasing the precision and reliability of height determination.