Volume XLI-B8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 771-777, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-771-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 771-777, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-771-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  23 Jun 2016

23 Jun 2016

AN OPTIONAL THRESHOLD WITH SVM CLOUD DETECTION ALGORITHM AND DSP IMPLEMENTATION

Guoqing Zhou1, Xiang Zhou2, Tao Yue1, and Yilong Liu3 Guoqing Zhou et al.
  • 1Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi, China
  • 2Department of Mechanical and Control Engineering,Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi, China
  • 3Getrag(Jiangxi) Transmission CO.Ltd, No.101 Jiaoqiao Road, Baishui Lake Industrial Park, Nanchang Economic and Technological Development Zone, Jiangxi, China

Keywords: cloud detection, DSP, SVM classifier, threshold, emulator

Abstract. This paper presents a method which combines the traditional threshold method and SVM method, to detect the cloud of Landsat-8 images. The proposed method is implemented using DSP for real-time cloud detection. The DSP platform connects with emulator and personal computer. The threshold method is firstly utilized to obtain a coarse cloud detection result, and then the SVM classifier is used to obtain high accuracy of cloud detection. More than 200 cloudy images from Lansat-8 were experimented to test the proposed method. Comparing the proposed method with SVM method, it is demonstrated that the cloud detection accuracy of each image using the proposed algorithm is higher than those of SVM algorithm. The results of the experiment demonstrate that the implementation of the proposed method on DSP can effectively realize the real-time cloud detection accurately.