Abstract
In order to make up the shortcomings of some existing ship target detection algorithms for high-resolution synthetic aperture radar (SAR) images, a ship target detection algorithm based on information theory and Harris corner detection for SAR images is proposed in this paper. Firstly, the SAR image is pretreated, and next, it is divided into superpixel patches by using the improved simple linear iterative clustering (SLIC) superpixel generation algorithm. Then, the self-information value of the superpixel patches is calculated, and the threshold T1 is set to select the candidate superpixel patches. And then, the extended neighborhood weighted information entropy growth rate threshold T2 is set to eliminate the false alarm candidate superpixel patches. Finally, the Harris corner detection algorithm is used to process the detection result and the number of the corner threshold T3 is set to filter out the false alarm patches, and the final SAR image target detection result is obtained. The effectiveness and superiority of the proposed algorithm are verified by comparing the proposed method with the results of constant false alarm rate (CFAR) detection algorithm combined with morphological processing algorithm and other ship target detection algorithms.
Highlights
Synthetic aperture radar imaging is not limited by weather, illumination, or other conditions
In order to improve the detection performance of the existing ship target detection method for highresolution synthetic aperture radar (SAR) images, a ship target detection algorithm based on information theory and Harris corner detection for high-resolution SAR images is proposed in this paper
For any superpixel patch Sn in SAR image I, assuming that the superpixel patch is composed of a × a pixels, the intensity distribution model of Sn can be expressed by the following formula:
Summary
Synthetic aperture radar imaging is not limited by weather, illumination, or other conditions. Wang et al [10] proposed a visual attention-based target detection method for high-resolution SAR images in complex scenes; even though the detection rate in complex is high, the original morphology of the targets cannot be well preserved in the final detection result. Have used the method based on multiscale variance weighted image entropy (MVWIE) method to detect the ship targets in the complex background SAR images They are proved to be effective to detect the true targets successfully; the discrimination of the target and the surrounding cells is difficult, and there are usually some false alarm targets in the detection result. In order to improve the detection performance of the existing ship target detection method for highresolution SAR images, a ship target detection algorithm based on information theory and Harris corner detection for high-resolution SAR images is proposed in this paper.
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