Multi-temporal satellite remote sensing images registration in mountainous forestland based on robust PCA

Peijing Zhang; Xiaoyan Luo; Junfan Liao

doi:10.1117/12.2573459

10 October 2020 Multi-temporal satellite remote sensing images registration in mountainous forestland based on robust PCA

Peijing Zhang, Xiaoyan Luo, Junfan Liao

Author Affiliations +

Proceedings Volume 11550, Optoelectronic Imaging and Multimedia Technology VII; 115500Y (2020) https://doi.org/10.1117/12.2573459
Event: SPIE/COS Photonics Asia, 2020, Online Only

Conference Poster

Abstract

The mountainous woodland covering with dense vegetation has complex terrain deformation, poor surface stability and rare obvious markers, which brings challenges to the accurate registration of multi-temporal remote sensing images. Viewing multi-temporal satellite image sequences as a whole matrix, we conduct RPCA matrix decomposition to generate a low-rank matrix and a sparse matrix, where the column of low rank matrix can be considered as the stable surface image. Referring to this, the original image registration is operated. It solves the difficulty to distinguish the real change of scenery and the distortion of remote sensing image in the case of unstable features and lack of obvious markers. Based on the feature matching method and local coordinate transformation and resampling model, the multi-temporal images are respectively registered with their stable surface images, and finally realize the batch accurate registration of multi-temporal satellite images of mountain forestland.

Conference Presentation

Citation Download Citation

Peijing Zhang, Xiaoyan Luo, and Junfan Liao "Multi-temporal satellite remote sensing images registration in mountainous forestland based on robust PCA", Proc. SPIE 11550, Optoelectronic Imaging and Multimedia Technology VII, 115500Y (10 October 2020); https://doi.org/10.1117/12.2573459

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