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:: Volume 4, Issue 4 (5-2015) ::
JGST 2015, 4(4): 161-174 Back to browse issues page
Improving the Classification Accuracy Using Combination of Target Detection Algorithms in Hyperspectral Images
S. A. Seyedain, M. J. Valadan Zoej, Y. Maghsoudi, M. Janalipour *
Abstract:   (4049 Views)
Hyperspectral images, with high spectral resolution, have caused vast progress in remote sensing extensions. One of the most important applications of these images is agriculture and forest. The purpose of this research is improvement in classification of various vegetation types over Botswana region by using combination of target detection algorithms and Hyperspectral image. In the first step, target detection algorithms implemented over the preprocessed Hyperspectral image. In the second step, information of target detection algorithms was combined by using the proposed method. Results of the proposed method were implemented for different windows size. The best overall accuracy of the method was 96.16 percent for 3*3 windows size that its overall accuracy has approximately improved at least 8 percent and uttermost 20 percent with respect to the results of target detection algorithms
Keywords: Hyperspectral image, Target detection algorithms, Vegetation, Combination of target detection algorithms
Full-Text [PDF 477 kb]   (1148 Downloads)    
Type of Study: Research | Subject: Photo&RS
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S. A. Seyedain, M. J. Valadan Zoej, Y. Maghsoudi, M. Janalipour. Improving the Classification Accuracy Using Combination of Target Detection Algorithms in Hyperspectral Images. JGST. 2015; 4 (4) :161-174
URL: http://jgst.issge.ir/article-1-170-en.html


Volume 4, Issue 4 (5-2015) Back to browse issues page
نشریه علمی علوم و فنون نقشه برداری Journal of Geomatics Science and Technology