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Target detection method by airborne and spaceborne images fusion based on past images

机译:基于过去图像的机载和星载图像融合目标检测方法

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To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.
机译:针对遥感目标检测方法对目标区域过去遥感数据利用率低,无法准确识别伪装目标的问题,提出了一种基于过去图像的机载和星载图像融合目标检测方法。 。将目标区域的空间遥感影像过去作为背景。融合机载和星载遥感数据,通过机载和星载图像配准,目标变化特征提取,背景噪声抑制和基于实时航空光学遥感图像的人工目标特征提取,提取目标特征。最后,支持向量机用于检测和识别特征融合数据上的目标。实验结果表明,该方法将机载和星载遥感图像的目标面积变化特征与目标检测算法相结合,对伪装和非伪装目标均具有良好的检测和识别效果。

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