基于对数比算子的星载SAR时序图像变化检测

Wenjie Shen, Yunzhen Jia, Yanping Wang, Yun Lin, Y. Li
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引用次数: 0

摘要

星载SAR具有稳定的重访周期,可以获得高分辨率图像。对于长时间序列图像,利用变化检测技术可以提取固定区域的变化信息。对环境监测、灾害损失评估和生产能力评估具有重要意义。现有的方法大多针对大面积,很少有目标级的变化检测方法。为此,本文提出了一种基于对数比算子的星载SAR时序图像变化检测方法,以获取目标级变化信息。该方法将序列中的一幅时间序列图像作为参考图像,通过对输入图像与参考图像的比值取对数得到变化图像。然后,利用CFAR算法完成对变化图像的检测。利用sentinel数据集对该方法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spaceborne SAR Time-Series Images Change Detection Based on Log-Ratio Operator
Spaceborne SAR has the advantage of stable revisit period to obtain high-resolution images. For the long-time time-series images, the change information in the fixed area can be extracted by using the change detection technology. It is of great significance for environmental monitoring, disaster loss assessment and production capacity assessment. Most of the existing methods are aimed at large areas, and there are few target-level change detection methods. Therefore, this paper proposes a Log-Ratio (LR) operator based change detection method using spaceborne SAR time-series images to obtain the target-level change information. In this method, one of the time-series images in the sequence is taken as the reference image, and the change image is obtained by taking logarithm of the ratio of the input and reference image. Then, the CFAR algorithm is used to complete the detection on the change image. The proposed method is verified by the Sentinel1 dataset.
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