Heterogenous Remote Sensing Image Registration based on Extended Phase Consistency Feature and Spatial Relationship Constraint

Fig. 1. Flowchart of heterosource remote sensing image registration algorithm based on extended phase coherence feature and spatial relationship constraints

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Fig. 2. The result of feature extraction

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Fig. 3. Flowchart of multi-scale weighted index map construction

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Fig. 4. Improved GLOH descriptor

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Fig. 5. Flowchart of the image registration method for the homography matrix iterative

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Fig. 6. Feature point matching maps of heterogenous images

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Fig. 7. Checkerboard mosaic images and enlarged sub-images of registration results

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Table 1. Table 1Basic information of experimental data

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Table 1. Table 1Basic information of experimental data

类别	组	影像平台	GSD(m)	大小/像素	日期	影像特点
光学—光学	1	GF1	2.0	960 $\times$ 1 030	07/2019	包含田地等弱纹理区域
	1	ZY3	2.1	1 060 $\times$ 1 160	05/2019	包含田地等弱纹理区域
	2	GF2	0.8	2 585 $\times$ 2 227	09/2019	地形复杂，起伏较大
	2	ZY3	2.1	1 480 $\times$ 1 030	07/2019	地形复杂，起伏较大
	3	GF1	2.0	651 $\times$ 651	07/2016	时相差异显著，分辨率差异较大
	3	GF2	1.0	651 $\times$ 651	04/2018	时相差异显著，分辨率差异较大
光学—Lidar	4	Airborne optical	2.5	524 $\times$ 524	06/2012	高层建筑，噪声干扰
	4	Lidar depth	2.5	524 $\times$ 524	06/2012	高层建筑，噪声干扰
	5	WorldView2	2	621 $\times$ 621	10/2011	噪声显著，时相差异
	5	Lidar intensity	2	621 $\times$ 617	10/2010	噪声显著，时相差异
	6	WorldView2	—	500 $\times$ 500	—	高层地物，受到噪声和阴影的干扰
	6	Lidar depth	—	500 $\times$ 500	—	高层地物，受到噪声和阴影的干扰
	7	Aerial image	3	550 $\times$ 550	07/2017	高层建筑物，受到噪声和阴影的干扰
	7	Lidar intensity	2	550 $\times$ 550	11/2017	高层建筑物，受到噪声和阴影的干扰
光学—SAR	8	Google Earth	3	500 $\times$ 500	11/2007	影像位于城市地区，噪声显著
	8	TerraSAR-X	3	500 $\times$ 500	12/2007	影像位于城市地区，噪声显著
	9	Google Earth	1	924 $\times$ 704	10/2012	较大的时相差异，影像包含噪声
	9	TerraSAR-X	1	900 $\times$ 795	12/2010	较大的时相差异，影像包含噪声
	10	Sentinel-2A	10	1 024 $\times$ 1 024	11/2020	弱纹理区域，影像具有明显的噪声
	10	Sentinel-1A	10	1 024 $\times$ 1 024	09/2020	弱纹理区域，影像具有明显的噪声

Table 2. Table 2Matching performance of different methods

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Table 2. Table 2Matching performance of different methods

算法	评价指标	组别
算法	评价指标	1	2	3	4	5	6	7	8	9	10
ASIFT	NCM	420	434	430	235	217	9	130	—	—	39
	DQ	2.343	1.797	1.517	1.623	2.172	1.841	2.006	—	—	1.362
	RMSE	1.12	2.36	2.08	2.23	2.42	3.56	3.68	—	—	2.72
SAR-SIFT	NCM	325	422	234	120	225	14	30	35	—	68
	DQ	2.623	1.597	1.725	1.723	1.663	1.647	1.826	1.432	—	1.142
	RMSE	1.42	3.25	2.68	2.82	2.73	2.32	2.62	2.43	—	3.69
HOPC	NCM	526	531	135	207	321	228	330	635	1627	184
	DQ	0.623	0.997	0.725	1.583	1.592	1.418	1.636	1.368	1.646	0.822
	RMSE	1.56	1.83	1.68	2.52	2.13	2.56	2.38	1.98	1.93	1.39
RIFT	NCM	766	631	535	227	421	390	230	1435	327	275
	DQ	0.994	0.797	0.594	0.623	1.142	0.641	1.006	0.984	0.878	0.669
	RMSE	1.03	2.12	2.63	1.26	2.28	1.88	2.13	2.12	2.12	1.89
OURS	NCM	1297	2200	299	357	565	465	308	595	427	383
	DQ	0.512	0.698	0.515	0.732	0.652	0.743	0.668	0.674	0.756	0.462
	RMSE	0.56	0.83	1.48	1.54	1.76	1.65	1.72	1.68	1.79	1.42

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Yao ZHENG, Shuwen YANG, Jinsha WU, Yukai FU, Ruixiong KOU. Heterogenous Remote Sensing Image Registration based on Extended Phase Consistency Feature and Spatial Relationship Constraint[J]. Remote Sensing Technology and Application, 2025, 40(1): 144

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Paper Information

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Received: Jul. 10, 2023

Accepted: --

Published Online: May. 22, 2025

The Author Email: Shuwen YANG (ysw040966@163.com)

DOI:10.11873/j.issn.1004-0323.2025.1.0144

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