Spectral and spatial feature integrated edge extraction method for high resolution remote sensing image

Qiqing Li; Jianwen Ma; Hasi Bagan; Xiuzhen Han; Zhili Liu

doi:10.1117/12.539837

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25 September 2003 Spectral and spatial feature integrated edge extraction method for high-resolution remote sensing image

Qiqing Li, Jianwen Ma, Hasi Bagan, Xiuzhen Han, Zhili Liu

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Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539837
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

Abstract

With urban and township development and E-Government program promotion in China city remote sensing as base data has developed rapidly. The technique demands in accuracy and effective edge detection and extraction from higher resolution image become important focal area. In the current popular image processing software packages there are some existing edge detection convolution kernels suchc as Sobel, Robert, Prewitt, Kirsch, Gauss-Laplace kernels. In general the kernels all work based on algorithm of convolution kernel in spatial territory of the image. However, satellite sensors capture spatial and spectral signatures of surfaces at same time. Use of both spatial and spectral features to establish a edge detection process is a new notion for achieving more accuracy results. In the paper we introduce a spatial and spectral integrated method which is designed in four stages. The result suggests that four stages process can achieve more cleanly and accuracy edges of city construction than that results of using other algorithms. The procedure is summarized in figure 1.

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Qiqing Li, Jianwen Ma, Hasi Bagan, Xiuzhen Han, and Zhili Liu "Spectral and spatial feature integrated edge extraction method for high-resolution remote sensing image", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539837

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