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A Hybrid Method for Multi-sensor Remote Sensing Image Registration Based on Salience Region

机译:基于显着区域的混合传感器遥感图像配准方法

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摘要

In order to align the remote sensing images, we propose a novel hybrid method that combines image segmentation and salient region detection, which is inspired by human vision system. First of all, we present a novel superpixel-based method for dividing the image into sub-areas. Second, we propose a novel method based on color and image textures for detecting salient regions composed by super-pixels. Then, we extract a new feature based on difference of Gaussian and local binary pattern from the salient regions. Finally, the sensed image is transformed by thin-plate spline. The proposed algorithm was tested on 30 pairs of remote sensing images and compared to other three state of the art methods. Experimental results show our approach is fast and robust, while still being efficient, which is better than other three methods.
机译:为了对齐遥感图像,我们提出了一种新颖的混合方法,该方法将图像分割和显着区域检测相结合,这是受人类视觉系统启发的。首先,我们提出了一种基于超像素的新颖方法,可将图像划分为多个子区域。其次,我们提出了一种基于颜色和图像纹理的新方法来检测由超像素组成的显着区域。然后,基于显着区域的高斯和局部二值模式的差异提取新特征。最终,通过薄板样条线变换感应到的图像。该算法在30对遥感图像上进行了测试,并与其他三种现有技术进行了比较。实验结果表明,该方法快速,鲁棒,同时仍然高效,优于其他三种方法。

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