Didi Zhao, Jiahui Li, Fenli Tan, Chenxin Zeng, Yiqun Ji. Remote Sensing Image Mosaic Based on Distribution Measure and Saliency Information[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410007
- Laser & Optoelectronics Progress
- Vol. 59, Issue 4, 0410007 (2022)
Fig. 1. Overall workflow of the two image stitching
Fig. 2. Distribution measure RANSAC algorithm
Fig. 3. Schematic of optimal inlier selection. (a) Tentative inliers Ck, |Ck|=231; (b) tentative inliers Ck+1, |Ck+1|=220; (c) Delaunay triangulation constructed according to Ck, Dk=3.474; (d) Delaunay triangulation constructed according to Ck+1, Dk+1=2.1361
Fig. 4. Schematic of saliency information extraction in remote sensing image. (a) Line segment detection result; (b) saliency information map
Fig. 5. Two-scale image fusion
Fig. 6. Three pairs of remote sensing images
Fig. 7. Quantitative analysis of algorithm performance. (a) MI; (b) FSIM
Fig. 8. Comparison of seamline detection and smooth transition fusion of four algorithms. (a) Seamline of Chon's algorithm; (b) seamline of HVDA algorithm; (c) seamline of QESE algorithm; (d) seamline of proposed algorithm; (e)‒(h) enlargements of corresponding box area
Fig. 9. Mosaic comparison of remote sensing sequence images. (a) AutoStitch; (b) ICE; (c) QESE; (d) proposed algorithm; (e)‒(h) enlargements of corresponding box area
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Table 1. Quantitative analysis of each algorithm for seamline detection and two-scale fusion
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