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《Geomatics & Spatial Information Technology》 2017-11
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Radiation of Remote Sensing Image Quality Assessment Based on Support Vector Machine( SVM) Method

YANG Fan;WANG Chao;ZHANG Han-chao;GUO Man;Liaoning Technical University;  
The rapid development of the contemporary photogrammetry and remote sensing technology,has been into the era of big data,how to obtain the huge amounts of digital image radiation quality evaluation is a serious problem. In three respects: information,clarity,grayscale distribution ten evaluation index as the image characteristics,the method of using support vector machine( SVM)learning supervision resources No. 3 as an example to evaluate the radiation quality of remote sensing image and the result analysis.Experimental results show that the method of the evaluation results with artificial evaluation results are consistent,high accuracy,and high degree of automation,suitable for application in remote sensing image quality evaluation of radiation.
【Fund】: 国家自然科学基金(50604009);; 辽宁省“百千万人才工程”人选资助项目(2010921099);; 辽宁省教育厅重点实验室基础研究项目(LJZS001)资助
【CateGory Index】: P237
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