Publications

Dou, HX; Zhang, MM; Wen, R; Chen, Y; Liu, J; Deng, LJ (2024). Remote Sensing Image Destriping by an _₀-Based Nonconvex Model With Overlapping Group Sparse Hyper-Laplacian Prior. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 21, 5505905.

Abstract
In this letter, we propose an & ell;0-based nonconvex optimization model with overlapping group sparse hyper-Laplacian (HL) prior (& ell;(0)-OGSHL) to remove stripes from remote sensing images (RSIs) effectively. Specifically, we utilize the HL prior with OGSHL to characterize the properties of the underlying image. In addition, the related & ell;(0)-quasi equivalent is transformed into an easily solvable form by employing a mathematical program with equilibrium constraints (MPEC).Furthermore, the alternating direction method of multipliers(ADMM) algorithm is employed for resolving the equivalent nonconvex optimization model, and the complex OGSHL sub-problem is addressed through the majorization-minimization(MM) method. Finally, the experimental results on the simulated datasets conclusively demonstrate the superior performance of the proposed method over the compared methods (with 1-3 dB higher MPSNR), both quantitatively and visually. The code will be available after possible acceptance.

DOI:
10.1109/LGRS.2024.3400225

ISSN:
1545-598X