Satellite cloud picture classification method and system

Abstract

The invention relates to a satellite cloud picture classification method and system, and the method comprises the steps: obtaining a plurality of reference satellite cloud pictures, and enabling eachreference satellite cloud picture to have a four-channel reference infrared image; marking and classifying each pixel position in the four-channel reference infrared image of each reference satellitecloud picture to obtain a reference label; modeling according to each reference infrared image and the corresponding reference label to obtain a classification network model; and according to the classification network model, identifying the four-channel external red image of the satellite cloud picture to be processed to obtain a corresponding category. According to the invention, the plurality of reference satellite cloud images are marked and classified, modeling is carried out according to the reference satellite cloud images and the reference labels to obtain the classification network model, the cloud image classification accuracy can be effectively improved according to the classification network model, and timely early warning is facilitated.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a satellite cloud image classification method and system. Background technique [0002] Satellite cloud images are top-down images of cloud cover and surface features on Earth observed by weather satellites. It mainly includes infrared cloud images, visible light cloud images and water vapor images. Satellite cloud images can be used to identify different weather systems, determine their location, estimate their strength and development trend, and provide a basis for weather analysis and weather forecasting. Especially in areas lacking meteorological observation stations such as oceans, deserts, and plateaus, the data provided by satellite cloud images make up for the lack of conventional detection data and play an important role in improving the accuracy of forecasting. [0003] Convolutional neural networks have achieved great success in the classification and segme...

AI Technical Summary

Problems solved by technology

[0003] Convolutional neural networks have achieved great success in the classification and segmentation of natural images, but the accuracy of applying deep learning methods to cloud classification in satellite images is relatively poor, which is not conducive to timely early warning

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