Target Detection in High-Resolution SAR Images via Searching for Part Models

In high-resolution synthetic aperture radar (SAR) images, targets are often spatially spread, and some separated regions of one target may be detected as different potential targets. The target should be represented by a part model to combine the separated regions into one target. In this letter, a part often means a separated region, and the part model obtains a hierarchical combination of the other parts. Moreover, the bottom hierarchy consists of strong scatters in the local SAR image, which are searched based on compressed intensities. The middle hierarchy consists of parts, which are generated based on connectivity and similarity of scatters in the bottom hierarchy. The top hierarchy delineates the relationship of parts in the middle hierarchy. A search method is designed based on the different features of the elements in each hierarchy. Consequently, the proposed algorithm combines different traits of targets to improve detection, and unites the separated regions of one target in the top hierarchy. This algorithm is validated by SAR images with different resolutions and scenes. scatters connectivity