Cloud detection in MODIS data based on spectrum analysis and snake model

Abstract

Clouds in satellite images must be precisely identified prior to any further analysis in any case. A new cloud detection algorithm based on spectrum analysis and snake model is put forward in this paper. According to the distinction of the spectral bands for the MODIS and the spectrum curve of different objects, we can differentiate the cloud from other objects well by the band1, band6 and band26. Because the distinct difference between cloud and the earth's surface, the detected thresholds have good robustness, and they are not sensitivity to images. Then we can optimize the cloud boundary by snake model. We adequately use the image information of the three bands in snake model via color gradient. By balancing these model-based and data-driven energy terms using regularization parameters, the snake algorithm can extract very accurate cloud boundaries without gaps and spurious branches. According to numerous experimental results, the new cloud detection algorithm in this paper is simple, feasible and suitable.