Remote Sensing Images Inpainting based on Structured Low-Rank Matrix Approximation

摘要

Due to the sensor malfunction or poor observation conditions, optical remote sensing images often suffer from information loss such as dead pixels or cloud contamination. We propose a remote sensing image inpainting method based on structured low-rank matrix approximation. The hybrid regularizations are applied to recover the piecewise constant and the piecewise linear components of the image separately by exploiting the low-rank properties of the structured Toeplitz matrices of the two image components. The corresponding optimization problem can be solved using the half-circulant approximation of the Toeplitz matrix. Experimental results demonstrate the efficacy of the proposed method.