Relative radiometric calibration precision will affect the application of satellite images, and hence high precision relative radiometric is very important. Nowadays, the ordinary radiometric calibration method of the thermal-infrared images is the on-orbit radiometric calibration which has fewer sample data and lower accuracy, therefore the result of on-orbit radiometric calibration can't satisfy the application requirement. In view of such a situation, a new radiometric calibration method of the thermal-infrared images based on classification and statistics is proposed in this paper. The new method adopts the original satellite images as sample data to calculate the parameters based on rich types of surface feature in satellite images to solve the problem of insufficient sample data of on-orbit radiometric calibration, meanwhile it introduces classification into the construction of the new calibration model by considering the different characteristics of photoelectric response function that the satellite payload will have in different radiometric energy so as to improve the precision of radiometric calibration. The experimental results show that the proposed method performs better than the ordinary on-orbit radiometric calibration method.
张炳先, 李岩, 何红艳. 基于在轨分类统计的热红外影像辐射校正方法[J]. 国土资源遥感, 2016, 28(4): 24-29.
ZHANG Bingxian, LI Yan, HE Hongyan. Radiometric calibration method of thermal-infrared images based on on-orbit classification and statistics. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(4): 24-29.
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