基于GMM的视频sar运动目标检测方法

Meng Yan, L. Li, Haochuan Chen
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引用次数: 0

摘要

在视频sar圆迹成像模式下,运动目标的能量会发生离焦和偏移。然而,由于目标高度的遮挡,在其真实位置存在阴影,代表能量不足。此外,VideoSAR图像序列的相邻帧之间存在很强的相关性,阴影也会随着目标的移动而移动。基于这一特性,提出了一种新的视频sar图像序列运动目标检测方法。该方法基于高斯混合模型。首先对图像序列进行预处理,使用sift + RANSAC算法和中值滤波处理,然后使用Otsu阈值分割算法将图像转换为二值图像,使用高斯混合模型检测运动目标,最后进行形态学处理。利用桑迪亚国家实验室的视频sar图像序列,可以有效地检测出运动目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A VideoSAR Moving Target Detection Method Based on GMM
In VideoSAR circle trace imaging mode, the energy of moving target is defocused and shifted. However, due to the occlusion of target height, there is shadow in its real position, which represents the lack of energy. In addition, there is a strong correlation between adjacent frames of VideoSAR image sequence, and the shadow also moves with the movement of the target. Based on this property, a new method for moving object detection in VideoSAR image sequences is proposed. This method is based on Gaussian mixture model. Firstly, it preprocesses the image sequence, uses sift + RANSAC algorithm and median filter processing, then uses Otsu threshold segmentation algorithm to transform the image into binary image, uses Gaussian mixture model to detect moving objects, and finally carries out morphological processing. Using VideoSAR image sequence of Sandia National Laboratory, the moving target can be detected effectively.
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