Robust Fine Registration of Multisensor Remote Sensing Images Based on Enhanced Subpixel Phase Correlation

Automatic fine registration of multisensor images plays an essential role in many remote sensing applications. However, it is always a challenging task due to significant radiometric and textural differences. In this paper, an enhanced subpixel phase correlation method is proposed, which embeds phase congruency-based structural representation, L1-norm-based rank-one matrix approximation with adaptive masking, and stable robust model fitting into the conventional calculation framework in the frequency domain. The aim is to improve the accuracy and robustness of subpixel translation estimation in practical cases. In addition, template matching using the enhanced subpixel phase correlation is integrated to realize reliable fine registration, which is able to extract a sufficient number of well-distributed and high-accuracy tie points and reduce the local misalignment for coarsely coregistered multisensor remote sensing images. Experiments undertaken with images from different satellites and sensors were carried out in two parts: tie point matching and fine registration. The results of qualitative analysis and quantitative comparison with the state-of-the-art area-based and feature-based matching methods demonstrate the effectiveness and reliability of the proposed method for multisensor matching and registration.

[1]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[2]  Peter Kovesi,et al.  Image Features from Phase Congruency , 1995 .

[3]  B. N. Chatterji,et al.  An FFT-based technique for translation, rotation, and scale-invariant image registration , 1996, IEEE Trans. Image Process..

[4]  Michael T. Orchard,et al.  A fast direct Fourier-based algorithm for subpixel registration of images , 2001, IEEE Trans. Geosci. Remote. Sens..

[5]  Hassan Foroosh,et al.  Extension of phase correlation to subpixel registration , 2002, IEEE Trans. Image Process..

[6]  William Scott Hoge,et al.  A subspace identification extension to the phase correlation method [MRI application] , 2003, IEEE Transactions on Medical Imaging.

[7]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[8]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[9]  Paul A. Viola,et al.  Alignment by Maximization of Mutual Information , 1997, International Journal of Computer Vision.

[10]  Baba C. Vemuri,et al.  Non-Rigid Multi-Modal Image Registration Using Cross-Cumulative Residual Entropy , 2007, International Journal of Computer Vision.

[11]  Qing Zhu,et al.  Seed point selection method for triangle constrained image matching propagation , 2006, IEEE Geoscience and Remote Sensing Letters.

[12]  Sébastien Leprince,et al.  Automatic and Precise Orthorectification, Coregistration, and Subpixel Correlation of Satellite Images, Application to Ground Deformation Measurements , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[13]  David A. Clausi,et al.  ARRSI: Automatic Registration of Remote-Sensing Images , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Georgios D. Evangelidis,et al.  Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Manuel Guizar-Sicairos,et al.  Efficient subpixel image registration algorithms. , 2008, Optics letters.

[16]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[17]  Tang Ping.  Automatic Registration of Remote Sensing Images Using Affine Invariant Features , 2009 .

[18]  Peter Reinartz,et al.  Mutual-Information-Based Registration of TerraSAR-X and Ikonos Imagery in Urban Areas , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Lionel Moisan,et al.  Periodic Plus Smooth Image Decomposition , 2011, Journal of Mathematical Imaging and Vision.

[20]  Gary R. Bradski,et al.  ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.

[21]  Youkyung Han,et al.  Automatic Registration of High-Resolution Images Using Local Properties of Features , 2012 .

[22]  Shuicheng Yan,et al.  Practical low-rank matrix approximation under robust L1-norm , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[23]  Mark R. Pickering,et al.  Robust Automatic Registration of Multimodal Satellite Images Using CCRE With Partial Volume Interpolation , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Ozy Sjahputera,et al.  GeoCDX: An Automated Change Detection and Exploitation System for High-Resolution Satellite Imagery , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[25]  Yacov Hel-Or,et al.  Matching by Tone Mapping: Photometric Invariant Template Matching , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Yongil Kim,et al.  Parameter Optimization for the Extraction of Matching Points Between High-Resolution Multisensor Images in Urban Areas , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Yuanxin Ye,et al.  A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences , 2014 .

[28]  Maoguo Gong,et al.  A Novel Coarse-to-Fine Scheme for Automatic Image Registration Based on SIFT and Mutual Information , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[29]  Yusheng Xu,et al.  A Novel Subpixel Phase Correlation Method Using Singular Value Decomposition and Unified Random Sample Consensus , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[30]  Javier-Flavio Vigueras,et al.  Phase correlation with sub-pixel accuracy: A comparative study in 1D and 2D , 2015, Comput. Vis. Image Underst..

[31]  Francesca Bovolo,et al.  An Approach to Fine Coregistration Between Very High Resolution Multispectral Images Based on Registration Noise Distribution , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Amin Sedaghat,et al.  Remote Sensing Image Matching Based on Adaptive Binning SIFT Descriptor , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[33]  A. S. Belward,et al.  Who launched what, when and why; trends in global land-cover observation capacity from civilian earth observation satellites , 2015 .

[34]  Carola-Bibiane Schönlieb,et al.  Nonparametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Wooded Landscapes , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[35]  Huanfeng Shen,et al.  Multimodal registration of remotely sensed images based on Jeffrey’s divergence , 2016 .

[36]  Qing Zhu,et al.  Stable least-squares matching for oblique images using bound constrained optimization and a robust loss function , 2016 .

[37]  Zhenwei Cao,et al.  Robust Model Fitting Using Higher Than Minimal Subset Sampling , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[38]  Haichao Li,et al.  Robust Multi-Source Image Registration for Optical Satellite Based on Phase Information , 2016 .

[39]  Lorenzo Bruzzone,et al.  Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[40]  Serhiy Skakun,et al.  Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping , 2017, Int. J. Digit. Earth.

[41]  Patrick Hostert,et al.  AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data , 2017, Remote. Sens..

[42]  Zhaoming Zhang,et al.  A Novel Image Registration Method Based on Phase Correlation Using Low-Rank Matrix Factorization With Mixture of Gaussian , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[43]  Bo Liu,et al.  Efficient subpixel registration for polarization-modulated 3D imaging. , 2018, Optics express.

[44]  Xiaorun Li,et al.  Medium-low resolution multisource remote sensing image registration based on SIFT and robust regional mutual information , 2018 .

[45]  André Stumpf,et al.  Improved Co-Registration of Sentinel-2 and Landsat-8 Imagery for Earth Surface Motion Measurements , 2018, Remote. Sens..

[46]  Yan Wu,et al.  SAR and Optical Image Registration Using Nonlinear Diffusion and Phase Congruency Structural Descriptor , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[47]  X. Tong,et al.  An Improved Subpixel Phase Correlation Method with Application in Videogrammetric Monitoring of Shaking Table Tests , 2018, Photogrammetric Engineering & Remote Sensing.

[48]  Guojin He,et al.  An Extension of Phase Correlation-Based Image Registration to Estimate Similarity Transform Using Multiple Polar Fourier Transform , 2018, Remote. Sens..

[49]  Wei Yuan,et al.  Matching Multi-Sensor Remote Sensing Images via an Affinity Tensor , 2018, Remote. Sens..

[50]  Junho Yeom,et al.  Improved Piecewise Linear Transformation for Precise Warping of Very-High-Resolution Remote Sensing Images , 2019, Remote. Sens..

[51]  Francesca Bovolo,et al.  A Fast and Robust Matching Framework for Multimodal Remote Sensing Image Registration , 2018, ArXiv.

[52]  Wenzhong Shi,et al.  Robust Multisource Remote Sensing Image Registration Method Based on Scene Shape Similarity , 2019 .

[53]  Chengcheng Guo,et al.  Illumination-Robust Subpixel Fourier-Based Image Correlation Methods Based on Phase Congruency , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[54]  Yongsheng Zhang,et al.  A Coarse-to-Fine Registration Strategy for Multi-Sensor Images with Large Resolution Differences , 2019, Remote. Sens..

[55]  Guojin He,et al.  Eliminating the Effect of Image Border with Image Periodic Decomposition for Phase Correlation Based Remote Sensing Image Registration † , 2019, Sensors.

[56]  Jianguo Liu,et al.  Phase Correlation Decomposition: The Impact of Illumination Variation for Robust Subpixel Remotely Sensed Image Matching , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[57]  Qingyun Du,et al.  Robust registration for remote sensing images by combining and localizing feature- and area-based methods , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[58]  Qian Du,et al.  Image Registration With Fourier-Based Image Correlation: A Comprehensive Review of Developments and Applications , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[59]  Xiaorun Li,et al.  A Novel Coarse-to-Fine Scheme for Remote Sensing Image Registration Based on SIFT and Phase Correlation , 2019, Remote. Sens..

[60]  Zhen Ye,et al.  Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study , 2020, Remote. Sens..

[61]  Qing Xu,et al.  Rank-Based Local Self-Similarity Descriptor for Optical-to-SAR Image Matching , 2020, IEEE Geoscience and Remote Sensing Letters.

[62]  Qingwu Hu,et al.  RIFT: Multi-Modal Image Matching Based on Radiation-Variation Insensitive Feature Transform , 2019, IEEE Transactions on Image Processing.

[63]  Fabio Bellavia,et al.  Is There Anything New to Say About SIFT Matching? , 2020, International Journal of Computer Vision.