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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >Infrared images target detection based on background modeling in the discrete cosine domain
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Infrared images target detection based on background modeling in the discrete cosine domain

机译：基于背景模型的离散余弦域红外图像目标检测

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Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.
机译：背景建模是检测视频监视运动目标的关键技术。大多数背景建模技术都是针对土地监测并在空间领域内进行的。当场景是复杂的波动海面时，很难建立背景。本文在离散余弦变换（DCT）域中，对目标之间的背景稳定性和可分离性进行了深入分析，在此基础上，提出了一种背景建模方法。所提出的方法将每个频率点建模为单个高斯模型来表示背景，并通过抑制背景系数来提取目标。实验结果表明，该方法可以建立准确的海水背景模型，并且在空间域上的检测结果优于其他背景建模方法。

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