Compressed Sensing-Based Inpainting of Aqua Moderate Resolution Imaging Spectroradiometer Band 6 Using Adaptive Spectrum-Weighted Sparse Bayesian Dictionary Learning

Abstract

Because of malfunction or noise in 15 out of the 20 detectors, band 6 (1.628-1.652 μm) of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Aqua satellite contains large areas of dead pixel stripes. Therefore, the corresponding high-level products of MODIS are corrupted by this periodic phenomenon. This paper proposes an improved Bayesian dictionary learning algorithm based on the burgeoning compressed sensing theory to solve this problem. Compared with other state-of-the-art methods, the proposed method can adaptively exploit the spectral relations of band 6 and other spectra. The performance of the proposed method is demonstrated by experiments on both simulated Terra and real Aqua images.