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Analysis of edge detection algorithms for feature extraction in satellite images

机译:卫星图像特征提取的边缘检测算法分析

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摘要

In field of image processing and pattern recognition, the use of edges as a feature is significant for feature extraction owing to its simplicity and accuracy. Its areas of application vary from object recognition to satellite based terrain recognition. There are many edge detection techniques like the canny edge detector and Sobel edge detector etc. However, the quality of an efficient algorithm depends on its capability to generate well localized edges of real images. Noise is inherent in all real images. To reduce its effect, various smoothing low pass filters are used prior to edge detection. This work, compares edge detection based on bilateral filtering with canny edge detection technique for satellite Images. Bilateral filtering based edge detection not only generates well localized edges but also simultaneously reduces considerable noise from real life images. The results show that the bilateral filtering based edge detection provide better edge maps than other comparable techniques.
机译:在图像处理和模式识别领域,由于边缘的简单性和准确性,将边缘用作特征对于特征提取具有重要意义。从物体识别到基于卫星的地形识别,其应用领域各不相同。有许多边缘检测技术,例如canny边缘检测器和Sobel边缘检测器等。但是,有效算法的质量取决于其生成真实图像定位良好的边缘的能力。噪点是所有真实图像中固有的。为了降低其影响,在边缘检测之前使用了各种平滑的低通滤波器。这项工作将基于双边滤波的边缘检测与卫星图像的Canny边缘检测技术进行了比较。基于双边滤波的边缘检测不仅可以生成定位良好的边缘,还可以同时减少来自现实生活图像的大量噪声。结果表明,与其他可比技术相比,基于双边滤波的边缘检测提供了更好的边缘图。

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