Classification of Ground-based Meteorological Cloud Images Based on Feature Selection Technique of Mutual Information F-statistics

Abstract

Abstract: In the study of cloud type recognition of ground-based meteorological cloud images, the feature selection technology based on Local Binary Pattern (LBP) descriptors is the most common method due to its simplicity and effectiveness. However, the high-dimensional property of LBP features makes the performance and computational overhead of cloud type recognition unsatisfactory. To the end, an LBP feature selection algorithm based on F-statistics constructed by mutual information is proposed, which can achieve effective dimensionality reduction of high-dimensional LBP features, while ensuring the accuracy of cloud type recognition, greatly reducing the computational cost of feature selection process.

Key words: ground-based meteorological cloud images, feature selection of high dimensional, mutual information, F-statistics, classification

YANG Qiu-liang, WANG Yu, YANG Xing-li, LI Ji-hong. Classification of Ground-based Meteorological Cloud Images Based on Feature Selection Technique of Mutual Information F-statistics [J]. Computer and Modernization, 2021, 0(02): 18-23.

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Classification of Ground-based Meteorological Cloud Images Based on Feature Selection Technique of Mutual Information F-statistics

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