Department of Geoinformatics and Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland.
Sensors (Basel). 2021 Mar 2;21(5):1706. doi: 10.3390/s21051706.
This article presents the results of automatic detection of subsidence troughs in synthetic aperture radar (SAR) interferograms. The detection of subsidence troughs is based on the circlet transform, which is able to detect features with circular shapes. Compared to other methods of detecting circles, the circular transform takes into account the finite data frequency. Moreover, the search shape is not limited to a circle but identified on the basis of a certain width. This is especially important in the case of detection of subsidence troughs whose shapes may not be similar to circles or ellipses but to their fragments. The transformation works directly on the image gradient; it does not require further binary segmentation or edge detection as in the case of other methods, e.g., the Hough transform. The entire processing process can be automated to save time and increase reliability compared to traditional methods. The proposed automatic detection method was tested on a differential interferogram that was generated based on Sentinel-1A SAR images of the Upper Silesian Coal Basin area. The test carried out showed that the proposed method is 20% more effective in detecting troughs that than the method using Hough transform.
本文提出了一种在合成孔径雷达（SAR）干涉图中自动检测沉降槽的方法。沉降槽的检测基于圆变换，该方法能够检测具有圆形特征的目标。与其他检测圆形的方法相比，圆变换考虑了有限的数据频率。此外，搜索形状不仅限于圆形，而是根据一定的宽度进行识别。这在检测沉降槽的形状可能不像圆形或椭圆形，而是它们的碎片时尤为重要。变换直接作用于图像梯度，不需要像其他方法（例如霍夫变换）那样进行进一步的二值分割或边缘检测。与传统方法相比，整个处理过程可以自动化，以节省时间并提高可靠性。所提出的自动检测方法在基于 Sentinel-1A SAR 图像的上西里西亚煤炭盆地地区生成的差分干涉图上进行了测试。所进行的测试表明，与使用霍夫变换的方法相比，该方法检测槽的效率提高了 20%。
