Cloud judgment method and system

Abstract

The invention discloses a cloud judgment method. The cloud judgment method comprises the steps that an image collected in advance is subjected to checkerboard segmentation processing to obtain a plurality of identical interpretation units; radiation information and texture information of the interpretation units are collected respectively, the radiation information and the texture information are compared with prestored radiation information and texture information of a desert, the radiation information and the texture information are not matched with the radiation information and the texture information of the desert, the radiation information and the texture information are compared with prestored radiation information and texture information of thick clouds, and on the condition that the radiation information and the texture information are matched with the radiation information and the texture information of the thick clouds, the cloud amount in the interpretation units is analyzed according to the radiation information and the texture information; the adjacent interpretation units containing cloud amount information are combined and expressed with a new layer; the total cloud amount information is output. The cloud judgment method has the advantages that when cloud detection and cloud information extraction are conducted on multispectral images through the method, the cloud judgment accurate rate reaches 88.6%, and the production efficiency is greatly improved.

Description

technical field [0001] The invention relates to the field of automatic interpretation of cloud amount of multi-spectral images, in particular to a method and system for cloud determination. Background technique [0002] In remote sensing images, cloud coverage reduces the quality and utilization of data to a great extent. Cloud detection is the basis and necessary link for remote sensing data processing and analysis, so it is a very meaningful research topic to accurately extract the cloud amount in a scene image. Early cloud detection and identification mainly relied on manual visual interpretation. This method is time-consuming, laborious, and has strong subjective limitations and empirical components. The accuracy is low, the efficiency is low, and it takes a lot of manpower to do this work, which seriously affects the progress of the entire process in the processing step of cloud detection. However, in recent years, as satellites with various resolutions have been la...

AI Technical Summary

Problems solved by technology

[0020] 1. Most of the methods rely on multispectral information, and are mainly aimed at meteorological satellites, and are not suitable for high-resolution panchromatic CCD images;

[0021] 2. The method is often aimed at specific satellite image products, and its universality is poor;

[0022] 3. The performance index of the method needs to be improved

Images