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High-resolution SAR image ship detection method based on visual attention mechanism

A visual attention mechanism, high-resolution technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as multiple false alarms, avoid false alarm problems, and improve real-time and accuracy.

Active Publication Date: 2017-10-20
NAVAL AVIATION UNIV
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Problems solved by technology

[0004] The present invention proposes a high-resolution SAR image ship detection method based on a visual attention mechanism, which aims to solve the problem of multiple false alarms in the existing SAR image target detection and meet the requirements of intelligent detection and real-time requirements

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Embodiment Construction

[0009] The technical scheme of a kind of high-resolution SAR image ship detection method based on visual attention mechanism proposed by the present invention comprises the following steps:

[0010] Step 1.1: The calculation model uses the salient region calculation algorithm of the global search method, which is a visual saliency region extraction method based on the frequency domain of the image, and is implemented by fast Fourier transform. Usually, there are Different from the part of the same shape, that is, the spectral residual part containing the target information, the visual saliency model will extract this residual part; assuming I(x) is an image, the spectral FFT[I(x)] of the image can be decomposed There are two parts into amplitude spectrum A(f) and phase spectrum P(f);

[0011] P(f)=FFT[I(x)] / |{FFT[I(x)]}| (1)

[0012] R(f)=BP(f)·P(f) (2)

[0013] S(f) = FFT -1 [R(f)] (3)

[0014] Among them, FFT and FFT -1 Represents the fast Fourier transform and its inve...

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Abstract

The invention discloses a high-resolution SAR image ship detection method based on a visual attention mechanism, and belongs to the field of radar image target detection. Mainly aiming at a problem that a conventional high-resolution SAR image target detection method cannot meet the demands of intelligent detection and the real-time requirements, the method comprises the steps: extracting a visual significant model of a frequency spectrum residual error part comprising target information in an image based on the frequency domain Fourier transform; carrying out the binarization processing of a saliency map and the extraction of an AOI (area of interest), analyzing and designing a local maximum posterior probability classifier to carry out the target detection of a target region from the angle of classification, and achieving the detection through a parameter estimation and decision criterion. The method can improve the ship detection real-time performance and accuracy through the high-resolution SAR image, and effectively solves a problem of higher false alarm in detection.

Description

technical field [0001] The invention belongs to the field of synthetic aperture radar image target detection, relates to a detection method that meets the real-time detection requirements of radar image targets, and is suitable for ship target detection and monitoring under complex sea conditions including a large number of uneven sea clutter areas and speckle noises. high-resolution synthetic aperture radar images. Background technique [0002] Synthetic aperture radar (SAR) has the characteristics of all-time, all-weather, and large range, and is an important part of ocean monitoring and surveillance, among which ship target detection has increasingly become a research hotspot. Ship target detection in SAR images is the premise and foundation of its classification and recognition, and is an important aspect of SAR image applications. [0003] With the launch and operation of new-generation SAR sensors such as Radarsat-2, TerraSAR-X, and Gaofen-3, SAR is gradually developi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/136G06K9/00G06K9/46G06K9/62
CPCG06T7/0004G06T7/11G06T7/136G06T2207/10044G06T2207/20104G06V20/13G06V10/462G06F18/2415
Inventor 徐永力熊伟崔亚奇姚力波吕亚飞刘恒燕朱洪峰
Owner NAVAL AVIATION UNIV
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