Heterogeneous Remote Sensing Image Matching Algorithm Based on Residual Pseudo-Siamese Convolution Cross-Correlation Network

Rongping Zou; Bin Zhu; Chenyang Wang; Yaoxuan Zhu; Yangdi Hu

doi:10.3788/LOP202259.1228002

[1] Li Y Y, Wu H, Chang X L et al. Multi-view stereo positioning error analysis based on spaceborne optics and SAR images[J]. Acta Optica Sinica, 38, 0528003(2018).

[2] Schmitt M, Tupin F, Zhu X X. Fusion of SAR and optical remote sensing data: challenges and recent trends[C], 5458-5461(2017).

[3] Han Z S, Wang C P, Fu Q et al. Remote sensing image mode translation by spatial disentangled representation based GAN[J]. Acta Optica Sinica, 41, 0728003(2021).

[4] Xie Z H, Liu J H, Sun H et al. Fast registration of visible light and synthetic aperture radar images[J]. Laser & Optoelectronics Progress, 57, 062803(2020).

[5] Suri S, Reinartz P. Mutual-information-based registration of TerraSAR-X and ikonos imagery in urban areas[J]. IEEE Transactions on Geoscience and Remote Sensing, 48, 939-949(2010).

[6] Simo-Serra E, Trulls E, Ferraz L et al. Discriminative learning of deep convolutional feature point descriptors[C], 118-126(2015).

[7] Mou L C, Schmitt M, Wang Y Y et al. A CNN for the identification of corresponding patches in SAR and optical imagery of urban scenes[C], 16868046(2017).

[8] Bürgmann T, Koppe W, Schmitt M. Matching of TerraSAR-X derived ground control points to optical image patches using deep learning[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 158, 241-248(2019).

[9] Merkle N, Auer S, Müller R et al. Exploring the potential of conditional adversarial networks for optical and SAR image matching[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 1811-1820(2018).

[10] Hughes L H, Marcos D, Lobry S et al. A deep learning framework for matching of SAR and optical imagery[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 169, 166-179(2020).

[11] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

[12] Lin M, Chen Q, Yan S C. Network in network[EB/OL]. https://arxiv.org/abs/1312.4400

[13] Briechle K, Hanebeck U D. Template matching using fast normalized cross correlation[J]. Proceedings of SPIE, 4387, 95-102(2001).

[14] Ioffe S, Szegedy C. Batch normalization: accelerating deep network training by reducing internal covariate shift[C], 448-456(2015).

[15] Laskar Z, Kannala J. Context aware query image representation for particular object retrieval[M]. Sharma P, Bianchi F M. Image analysis, 10270, 88-99(2017).

[16] Schmitt M, Hughes L H, Zhu X X. The SEN1-2 dataset for deep learning in SAR-optical data fusion[EB/OL]. https://arxiv.org/abs/1807.01569

[17] Paszke A, Gross S, Massa F et al. PyTorch: an imperative style, high-performance deep learning library[EB/OL]. https://arxiv.org/abs/1912.01703

[18] Zhang K P, Zhang Z P, Li Z F et al. Joint face detection and alignment using multitask cascaded convolutional networks[J]. IEEE Signal Processing Letters, 23, 1499-1503(2016).