کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1764770 | 1020071 | 2012 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Watershed image segmentation and cloud classification from multispectral MSG-SEVIRI imagery
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موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علوم فضا و نجوم
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چکیده انگلیسی
In this work a technique for cloud detection and classification from MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infra-red Imager) imagery is presented. It is based on the segmentation of the multispectral images using order-invariant watershed algorithms, which are applied to the corresponding gradient images, computed by a multi-dimensional morphological operator. To reduce the over-segmentation produced by the watershed method, a RAG (Region Adjacency Graph) based region merging technique is applied, using region dissimilarity functions. Once the objects present in the image have been segmented, they are classified using a multi-threshold method based on physical considerations that takes into account the statistical parameters inside each region.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Space Research - Volume 49, Issue 1, 1 January 2012, Pages 135-142
Journal: Advances in Space Research - Volume 49, Issue 1, 1 January 2012, Pages 135-142
نویسندگان
Albano González, Juan C. Pérez, Jonathan Muñoz, Zebensui Méndez, Montserrat Armas,