Cloud detection technology based on Gaussian mixture model for 
high-resolution remote sensing imagery

doi:10.3969/j.issn.1000-2006.201708009

Cloud detection technology based on Gaussian mixture model for high-resolution remote sensing imagery

YANG Fan, ZHAO Zengpeng, ZHANG Lei

Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 2018, Vol. 42 ›› Issue (04) : 134-140.

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Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 2018, Vol. 42 ›› Issue (04) : 134-140. DOI: 10.3969/j.issn.1000-2006.201708009

Cloud detection technology based on Gaussian mixture model for high-resolution remote sensing imagery

YANG Fan, ZHAO Zengpeng^*, ZHANG Lei

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Abstract

Abstract: 【Objective】 Developing cloud detection technology for high-resolution remote-sensing images is difficult, especially for thin edge and scattered clouds. We used morphological operations and polygon simplification techniques to accurately extract cloud-containing, high-resolution remote-sensing images.【Method】First, the Gaussian low-pass filter was used to smooth the image and create uniform shading. The image was then divided into three categories: cloudy, partly cloudy and cloudless. The Otsu threshold method was used on cloudy images, and Gaussian mixture model segmentation was used on partly cloudy images. Finally, the cloud area was morphologically processed to determine the final cloud area. 【Result】The high-resolution remote-sensing image cloud-detection algorithm based on Otsu threshold segmentation and Gaussian mixture model has good visual effect and can effectively improve the accuracy of cloud detection. The accuracy rate is 98.60%, recall rate of the method is approximately 90%, and the error rate is approximately 2.58%. It can accurately detect thick, thin and scattered clouds, and can also effectively reduce the misidentification of houses, roads and bare land. 【Conclusion】The high-resolution remote-sensing image cloud-detection algorithm based on Otsu threshold segmentation and Gaussian mixture model is moderately complex, and has a small computation size, fast operation speed, high-precision detection and wide applicability.

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YANG Fan, ZHAO Zengpeng, ZHANG Lei. Cloud detection technology based on Gaussian mixture model for high-resolution remote sensing imagery[J]. Journal of Nanjing Forestry University (Natural Sciences Edition）. 2018, 42(04): 134-140 https://doi.org/10.3969/j.issn.1000-2006.201708009

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