An Integrated Approach for SAR Image Speckle Reduction and Target Detection

Speckle reduction and target detection are usually two independent and successive procedures in SAR information pro-cessing systems. The separated implementation scheme makes the determination of a suitable combination of speckle filter and target detector a challenging task in practice. This work attempts to propose a novel integrated approach for both SAR speckle reduction and target detection. It mainly contains three-fold. Firstly, a new representation in terms of the context scattering vector and context covariance matrix is established for information augmentation and mining for SAR data. Then, similar pixels within a large moving window are selected using matrix similarity test and the similar pixel number (SPN) is recorded. The speckle reduction can be conducted with the determined similar samples and salient targets (e.g. manmade targets) can be detected with the SPN index simultaneously. Finally, the speckle reduction and ship detection integrated processing procedure is established. Experimental studies are carried out with real space-borne SAR datasets and the proposed integrated framework shows superiority in both speckle reduction and target de-tection performances from visual and quantitative investigations.