多时相遥感影像变化检测算法研究

本文首次将非下采样Contourlet变换和上下截集模糊Kohonen聚类网络相结合,提出了一种无监督的多时相遥感影像变化检测算法。该算法采用非下采样Contourlet变换提取与对数比图像中的每个像素相对应的多尺度和多方向纹理,并采用上下截集模糊Kohonen聚类网络将这些多尺度和多方向纹理分为变化类与未变化类两类,最终得到变化检测图像。实验结果表明,与传统方法相比,对于高斯和斑点噪声,该算法具有更高的抗噪性能和检测精确度。

Change detection in multi-temporal satellite images

An unsupervised multi-scale change detection algorithm in multi-temporal satellite images is proposed in this paper.This method makes a combination of both nonsubsampled contourlet transform and up-down-set fuzzy Kohonen clustering network,and applies it to change detection initially.For each pixel in the log-ratio image,multi-scale and multi-direction feature vector is extracted using nonsubsampled contourlet transform.The final change detection map is achieved by clustering the multi-scale and multi-direction feature vectors using up-down-set fuzzy Kohonen clustering network into two classes：changed and unchanged.Experimental results demonstrate that the proposed method has a higher stability and accuracy against Gaussian and speckle noise comparing with traditional algorithms.