An Adaptive Weighted Tensor Completion Method for the Recovery of Remote Sensing Images with Missing Data

Kwok Po NG, Qiangqiang Yuan*, Li Yan, Jing Sun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)

Abstract

Missing information, such as dead pixel values and cloud effects, is very common image quality degradation problems in remote sensing. Missing information can reduce the accuracy of the subsequent image processing, in applications such as classification, unmixing, and target detection, and even the quantitative retrieval process. The main aim of this paper is to study an adaptive weighted tensor completion (AWTC) method for the recovery of remote sensing images with missing data. Our idea is to collectively make use of the spatial, spectral, and temporal information to build a new weighted tensor low-rank regularization model for recovering the missing data. In the model, the weights are determined adaptively by considering the contribution of the spatial, spectral, and temporal information in each dimension. Experimental results based on both simulated and real data sets are presented to verify that the proposed method can recover missing data, and its performance is found to be better than the other tested methods. In the simulated experiments, the peak signal-to-noise ratio is improved by more than 3 dB, compared with the original tensor completion model. In the real data experiments, the proposed AWTC model can better recover the dead line problem in Aqua Moderate Resolution Imaging Spectroradiometer band 6 and the scan-line corrector-off problem in enhanced thematic mapper plus images, with the smallest spectral distortion.

Original languageEnglish
Article number7878527
Pages (from-to)3367-3381
Number of pages15
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume55
Issue number6
DOIs
Publication statusPublished - Jun 2017

Scopus Subject Areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

User-Defined Keywords

  • Adaptive weighted
  • missing data reconstruction
  • remote sensing
  • tensor completion

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