Remote Sensing Image Cloud Identification of Cooperation with U-Net and Hidden Markov Model
Cloud and fog cover is one of the important factors affecting the utilization rate of optical remote sensing image forestry monitoring.In view of the problems that the traditional cloud recognition method is sensitive to noise and the Deep Learning method is not accurate in cloud edge recognition,a remote sensing image cloud recognition method of cooperation with U-Net and Hidden Markov Model is proposed in this paper.Firstly,the cloud is preliminarily identified based on the U-Net network structure to improve the sensitivity of the traditional method to noise.Secondly,it uses the Hidden Markov Model for back-end processing to optimize the edge contour of cloud recognition.The experimental results show that the accuracy of the remote sensing image cloud recognition method of cooperation with U-Net and Hidden Markov Model is improved by 5%compared with the traditional method.At the same time,the edge contour of the cloud is better preserved.
remote sensing imagecloud identificationU-Net Neural NetworkHidden Markov Model
国家科技期刊平台
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