Remote sensing image cloud detection method based on deep learning

Abstract

The invention discloses a remote sensing image cloud detection method based on deep learning. The method comprises the steps that image preprocessing is performed on an obtained remote sensing image dataset, and preprocessed images are divided into a training set and a test set; the images in the training set are used as input of a neural network model, and network model parameters are continuously updated to optimize the neural network model; and the images in the test set are input into the trained neural network model for verification, and cloud parts in the remote sensing images are detected. According to the method, on the basis of using a deep learning convolutional neural network in combination, the problem that a detection result is not ideal because cloud feature extraction is notsufficient is solved, detection precision is improved, and the universality of an algorithm is enhanced.

Description

technical field [0001] The invention relates to the fields of image processing, deep learning and target detection, in particular to a remote sensing image cloud detection method based on deep learning. Background technique [0002] In recent years, with the development of remote sensing image acquisition technology, remote sensing images have been widely used in various fields. In order to better interpret image information, clouds appearing above ground targets due to weather factors have become a research hotspot. The problem of cloud detection in remote sensing images can be regarded as a binary segmentation problem in image analysis. Satellite cloud images are ever-changing, and factors such as cloud height, thickness, type, and solar altitude angle will have a great impact on clouds. At present, the detection methods can be divided into the following categories. [0003] The method of physical detection is to use multi-spectral physical characteristics to apply to a ...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a remote sensing image cloud detection method based on deep learning in view of the deficiencies of the existing technology, using deep learning methods to deeply mine the feature information of clouds in remote sensing images, and to overcome the disadvantages of the original detection technology. The shortcomings of feature extraction are not deep enough to improve the detection accuracy and the universality of the algorithm

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