CFAR (Constant False Alarm Rate) and sparse representation-based high-resolution SAR (Synthetic Aperture Radar) image ship detection method

Abstract

The invention discloses a CFAR (Constant False Alarm Rate) and sparse representation-based high-resolution SAR (Synthetic Aperture Radar) image ship detection method, which mainly solves the problems of large data quantity to be processed and low real-time property existing in the conventional method. The method comprises the following detection steps: selecting a ship target training sample in a high-resolution SAR image and determining the size of a CFAR sliding window by the training sample; down-sampling the high-resolution image, performing image segmentation and land elimination on the high-resolution image, detecting in a low-resolution image by using the CFAR method and performing preliminary identification, and mapping a detected pixel point to a potential target region in the original high-resolution image; outputting potential target region slices obtained by all detection; and finally, extracting characteristic vectors of the potential target region slices respectively and identifying through a sparse representation classifier to obtain a final ship detection result. The CFAR and sparse representation-based high-resolution SAR image ship detection method has the advantages of high detection speed, high detection rate and low false alarm rate, and can be used for fishery supervision, maritime safety management and the like.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and relates to a SAR image ship detection method, which can be used for fishery supervision and maritime safety management. Background technique [0002] Ship detection is of great significance to fishery supervision and maritime safety management. Since Synthetic Apertuer Radar (SAR) has the advantages of all-weather and all-weather, the research on automatic target recognition technology of SAR image has been continuously It is one of the hotspots in the remote sensing neighborhood. [0003] Target detection is the basis of target recognition, and the main task of ship detection is to locate the positions of all ships and false alarms in a scene, and perform identification processing to eliminate false alarms, and finally output slices of ship targets for later Identify jobs. [0004] At present, there are a variety of practical ship target detection systems, such as t...

AI Technical Summary

Problems solved by technology

[0006] In the traditional CFAR-based SAR image ship target detection method, it is necessary to manually set the size of the sliding window and the width of the protection area, and these parameters are actually based on the manual estimation of the target information in the image. That is to say, the traditional CFAR-based SAR image ship detection method is actually a semi-automatic detection method; secondly, due to the different SAR image imaging parameters and scenes, the adaptiveness of the designed algorithm is low; in addition, in In the identification stage of the traditional SAR image ship detection method, the quadratic distance discriminator QDD proposed by Lincoln Laboratory is usually used. During the mapping process of the discriminator from the n-dimensional feature space to the one-dimensional distance space, the discriminative performance will decrease , resulting in poor performance of the overall detection results

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