A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-Camera
Aerial optical cameras are the primary method for capturing high-resolution images to produce large-scale mapping products. To improve aerial photography efficiency, multiple cameras are often used in combination to generate large-format virtual central projection images. This paper presents a high-...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/4/683 |
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| author | Xingzhou Luo Haitao Zhao Yaping Liu Nannan Liu Jiang Chen Hong Yang Jie Pan |
| author_facet | Xingzhou Luo Haitao Zhao Yaping Liu Nannan Liu Jiang Chen Hong Yang Jie Pan |
| author_sort | Xingzhou Luo |
| collection | DOAJ |
| description | Aerial optical cameras are the primary method for capturing high-resolution images to produce large-scale mapping products. To improve aerial photography efficiency, multiple cameras are often used in combination to generate large-format virtual central projection images. This paper presents a high-precision method for directly transforming raw images obtained from a dual-camera system mounted at an oblique angle into virtual central projection images, thereby enabling the construction of low-cost, large-format aerial camera systems. The method commences with an adaptive sub-block in the overlapping regions of the raw images to extract evenly distributed feature points, followed by iterative relative orientation to improve accuracy and reliability. A global projection transformation matrix is constructed, and the sigmoid function is employed as a weighted distance function for image stitching. The results demonstrate that the proposed method produces more evenly distributed feature points, higher relative orientation accuracy, and greater reliability. Simulation analysis of image overlap indicates that when the overlap exceeds 7%, stitching accuracy can be better than 1.25 μm. The aerial triangulation results demonstrate that the virtual central projection images satisfy the criteria for the production of 1:1000 scale mapping products. |
| format | Article |
| id | doaj-art-c0be280666e749eba06aa9350a408e38 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-c0be280666e749eba06aa9350a408e382025-08-20T03:12:01ZengMDPI AGRemote Sensing2072-42922025-02-0117468310.3390/rs17040683A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-CameraXingzhou Luo0Haitao Zhao1Yaping Liu2Nannan Liu3Jiang Chen4Hong Yang5Jie Pan6Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaShanghai Hangyao Information Technology Co., Ltd., Shanghai 200083, ChinaShanghai Hangyao Information Technology Co., Ltd., Shanghai 200083, ChinaShanghai Hangyao Information Technology Co., Ltd., Shanghai 200083, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerial optical cameras are the primary method for capturing high-resolution images to produce large-scale mapping products. To improve aerial photography efficiency, multiple cameras are often used in combination to generate large-format virtual central projection images. This paper presents a high-precision method for directly transforming raw images obtained from a dual-camera system mounted at an oblique angle into virtual central projection images, thereby enabling the construction of low-cost, large-format aerial camera systems. The method commences with an adaptive sub-block in the overlapping regions of the raw images to extract evenly distributed feature points, followed by iterative relative orientation to improve accuracy and reliability. A global projection transformation matrix is constructed, and the sigmoid function is employed as a weighted distance function for image stitching. The results demonstrate that the proposed method produces more evenly distributed feature points, higher relative orientation accuracy, and greater reliability. Simulation analysis of image overlap indicates that when the overlap exceeds 7%, stitching accuracy can be better than 1.25 μm. The aerial triangulation results demonstrate that the virtual central projection images satisfy the criteria for the production of 1:1000 scale mapping products.https://www.mdpi.com/2072-4292/17/4/683large-format cameraprojection transformationvirtual central projectionimage stitchingadaptive sub-block |
| spellingShingle | Xingzhou Luo Haitao Zhao Yaping Liu Nannan Liu Jiang Chen Hong Yang Jie Pan A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-Camera Remote Sensing large-format camera projection transformation virtual central projection image stitching adaptive sub-block |
| title | A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-Camera |
| title_full | A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-Camera |
| title_fullStr | A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-Camera |
| title_full_unstemmed | A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-Camera |
| title_short | A High-Precision Virtual Central Projection Image Generation Method for an Aerial Dual-Camera |
| title_sort | high precision virtual central projection image generation method for an aerial dual camera |
| topic | large-format camera projection transformation virtual central projection image stitching adaptive sub-block |
| url | https://www.mdpi.com/2072-4292/17/4/683 |
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