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PERFORMANCE ANALYSIS ON EDGE DETECTION ALGORITHMS FOR COASTLINE IMAGE DETECTION

机译:边缘图像检测边缘检测算法的性能分析

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摘要

Edge detection is one of the most important areas in the image analysis. Since edge detectors are not at ease applying to different situations, it would be ideal to find out edge detectors that work best in analysing satellite images. In this paper we evaluate the performance of commonly used edge detection algorithms for extracting coastlines over satellite images. The edge detection algorithms applied in this study are: Prewitt, Sobel, Canny and Morphological method. A labeling method is applied to the images before the edge detectors are used for coastline detection. Our comprehensive evaluation on the performance of these algorithms in detecting coastlines over the satellite images suggests that the Sobel edge detector offers the best performance. In the paper to measure the quality of the coastlines detected over the processed images after pruning, the Peak Signal to Noise Ration (PSNR) and Root Mean Square Error (RMSE) parameters are applied upon the images generated by each edge detection algorithm.
机译:边缘检测是图像分析中最重要的领域之一。由于边缘检测器不适用于不同情况,因此理想的方法是找出在分析卫星图像方面最有效的边缘检测器。在本文中,我们评估了用于提取卫星图像上海岸线的常用边缘检测算法的性能。在这项研究中应用的边缘检测算法是:Prewitt,Sobel,Canny和形态学方法。在将边缘检测器用于海岸线检测之前,将标记方法应用于图像。我们对这些算法在检测卫星图像上海岸线的性能方面的综合评估表明,Sobel边缘检测器可提供最佳性能。为了测量修剪后在经过处理的图像上检测到的海岸线的质量,将峰值信噪比(PSNR)和均方根误差(RMSE)参数应用于每种边缘检测算法生成的图像。

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