尺度空间Radon变换

D. Ziou, Nafaa Nacereddine, A. Goumeidane
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引用次数: 6

摘要

提出了利用捕获用户需求的度量函数对Radon变换进行扩展。这种新的变换称为尺度空间Radon变换,专门用于图像中嵌入的形状不是丝状的情况。以直线和椭圆为例,深入分析了在尺度空间和噪声存在下的SSRT行为。为了证明所提出的变换的有效性,首先对在模糊和噪声等强变化条件下合成的线性和椭圆结构进行了实验,然后对来自实际应用的结构图像进行了实验,如道路交通、卫星图像和焊缝x射线成像。在检测精度和计算时间方面,与知名变换和最近致力于此目的的工作进行了比较,其中所提出的变换在检测上述结构和准确定位其空间位置方面表现出色,即使在低质量图像中也是如此。
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Scale space Radon transform
An extension of Radon transform by using a measure function capturing the user need is proposed. The new transform, called scale space Radon transform, is devoted to the case where the embedded shape in the image is not filiform. A case study is brought on a straight line and an ellipse where the SSRT behaviour in the scale space and in the presence of noise is deeply analyzed. In order to show the effectiveness of the proposed transform, the experiments have been carried out, first, on linear and elliptical structures generated synthetically subjected to strong altering conditions such blur and noise and then on structures images issued from real-world applications such as road traffic, satellite imagery and weld X-ray imaging. Comparisons in terms of detection accuracy and computational time with well-known transforms and recent work dedicated to this purpose are conducted, where the proposed transform shows an outstanding performance in detecting the above-mentioned structures and targeting accurately their spatial locations even in low-quality images.
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