A Weighted Overlapped Block-Based Compressive Sensing in SAR Imaging

The compressive sensing (CS) theory has been widely used in synthetic aperture radar (SAR) imaging for its ability to reconstruct image from an extremely small set of measurements than what is generally considered necessary. Because block-based CS approaches in SAR imaging always cause block boundaries between two adjacent blocks, resulting in namely the block artefacts. In this paper, we propose a weighted overlapped block-based compressive sensing (WOBCS) method to reduce the block artefacts and accomplish SAR imaging. It has two main characteristics: 1) the strategy of sensing small and recovering big and 2) adaptive weighting technique among overlapped blocks. This proposed method is implemented by the well-known CS recovery schemes like orthogonal matching pursuit (OMP) and BCS-SPL. Promising results are demonstrated through several experiments.