Optical and SAR Image Registration Method of Coupling Phase Congruency and Mutual Information

Qing Xue; Shuwen Yang; Heng Yan; Liri Zang; Yukai Fu

doi:10.3788/LOP202259.2428003

Journals >Laser & Optoelectronics Progress >Volume 59 >Issue 24 >Page 2428003 > Article

Laser & Optoelectronics Progress
Vol. 59, Issue 24, 2428003 (2022)

Optical and SAR Image Registration Method of Coupling Phase Congruency and Mutual Information

Qing Xue¹, Shuwen Yang^1,2,3,*, Heng Yan¹, Liri Zang¹, and Yukai Fu¹

Author Affiliations

¹Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China

²National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, Gansu, China

³Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, Gansu,China

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DOI: 10.3788/LOP202259.2428003 Cite this Article Set citation alerts

Qing Xue, Shuwen Yang, Heng Yan, Liri Zang, Yukai Fu. Optical and SAR Image Registration Method of Coupling Phase Congruency and Mutual Information[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2428003 Copy Citation Text

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Fig. 1. Registration flow chart

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Fig. 2. Schematic of feature detection

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Fig. 3. MIM construction

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Fig. 4. Template matching

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Fig. 5. Comparison of matching effect under different template radius. (a) Case 1; (b) case 2; (c) case 3; (d) case 4

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Fig. 6. Matching effect diagrams. (a) Case 1; (b) case 2; (c) case 3; (d) case 4

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Fig. 7. Checkerboard mosaic of experimental registration. (a) Case 1; (b) case 2; (c) case 3; (d) case 4

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Case	Reference image	GSD /m	Size /pixel	Date	Image characteristic
Case	Sensed image	GSD /m	Size /pixel	Date	Image characteristic
Case 1	Sentinel-1A	10	1024 $\times$ 1024	2020-11	Complex terrain with large undulations
Case 1	Sentinel-2A	10	1024 $\times$ 1024	2020-11	Complex terrain with large undulations
Case 2	Google	3	500 $\times$ 500	2007-11	High buildings and significant noise
Case 2	TerraSAR-X	3	500 $\times$ 500	2007-12	High buildings and significant noise
Case 3	Google	3	628 $\times$ 618	2009-03	Have a temporal difference of 14 months
Case 3	TerraSAR-X	3	628 $\times$ 618	2008-01	Have a temporal difference of 14 months
Case 4	Google	1	512 $\times$ 512		Cover weakly textured area of farmland
Case 4	GF3	1	512 $\times$ 512		Cover weakly textured area of farmland

Table 1. Data description of test images

Case	Method	$N_{M a t c h e d C P s}$	$N_{C o r r e s p o n d i n g P o i n t s}$	CMR /%	RMSE /pixel
Case 1	Proposed method	900	476	52.89	1.34
	MI	900	280	31.11	5.4
	OS-SIFT	290	0	0
	RIFT	1494	79	5.29	3.90
Case 2	Proposed method	399	391	97.99	0.87
	MI	399	307	76.94	3.15
	OS-SIFT	303	73	24.09	4.58
	RIFT	1456	433	29.74	1.91
Case 3	Proposed method	400	399	99.75	0.83
	MI	400	366	91.5	2.50
	OS-SIFT	250	0	0
	RIFT	2036	672	33.01	2.19
Case 4	Proposed method	397	391	98.49	1.18
	MI	397	304	75.31	1.95
	OS-SIFT	103	27	26.21	4.03
	RIFT	844	132	15.64	2.90