Cloud classification research based on over complete dictionary sparse representation
HUANG Min
WANG Jia-li
Abstract：Aimed at the problem that automatic identification method for the cloud categories was less at present,a new method of cloud classification based on sparse representation of overcomplete dictionary was proposed.The method used different cloud types samples to establish an adaptive overcomplete dictionary, extracted dictionary features and designed sparse classifier to determine the type of cloud.The simulation a-nalysis results showed that the classification accuracy of Ca,Cs&Cd,As&Ac,Ns&Cu,Cb were 100%,63. 5%,90.3%,94.1%,98.2%,respectively.The overall classification accuracy was 89.2%.The classi-fication accuracy was higher than the support vector machine classifier and the traditional sparse represen-tation classifier.
Keywords：satellite cloudsparse representationovercomplete dictionary
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 82-85 )