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Improving the Classification Accuracy Using Combination of Target Detection Algorithms in Hyperspectral Images
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S. A. Seyedain   , M. J. Valadan Zoej , Y. Maghsoudi , M. Janalipour * |
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Abstract: (6777 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 |
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| Keywords: Hyperspectral image, Target detection algorithms, Vegetation, Combination of target detection algorithms |
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Full-Text [PDF 477 kb]
(1968 Downloads)
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Type of Study: Research |
Subject:
Photo&RS
Received: 2014/10/7
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