Modified Morphological Component Analysis Method for SAR Image Clutter Suppression - Shuangying Xiao; Huaping Xu; Bing Sun; Wei Liu (Remote Sensing)
The morphological component analysis (MCA) method can be used to suppress the clutter in a synthetic aperture radar (SAR) image when the dictionaries of clutter and target components are mutually incoherent. However, the effectiveness of the conventional MCA method may be reduced since the mutual incoherence assumption is difficult to fulfill in practice. To overcome the problem, a modified MCA method is proposed in this paper. The proposed method formulates clutter suppression as a constraint optimization problem that combines MCA with incoherence constraint and <semantics>L0</semantics> gradient minimization, and it presents an effective solution to the optimization problem. Specifically, the incoherence constraint of image components is designed to decorrelate different components and better separate targets from clutter. Meanwhile, the <semantics>L0</semantics> gradient minimization constraint is applied to further reduce the artifacts and preserve edges. Then, the optimization problem of the modified MCA is split into solvable subproblems to obtain the target image. Finally, experimental results from real images are carried out to demonstrate the effectiveness of the proposed clutter suppression method.