کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4687797 | 1635688 | 2008 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Solution of Multiple-Point Statistics to Extracting Information from Remotely Sensed Imagery
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information. Therefore, there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery. In the current article, a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification. The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese Yellow River delta on August 8, 1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier (MLC).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of China University of Geosciences - Volume 19, Issue 4, August 2008, Pages 421-428
Journal: Journal of China University of Geosciences - Volume 19, Issue 4, August 2008, Pages 421-428
نویسندگان
Ge Yong, Bai Hexiang, Cheng Qiuming,