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Measure for the Difference Between LBP Features Extracted From Original and Resized Cloud Images With Varying Resolutions
Wang, Yu1,2,3; Shi, Cunzhao1; Wang, Chunheng1; Xiao, Baihua1
Source PublicationIEEE GEOSCIENCE AND REMOTE SENSING LETTERS
2017-07-01
Volume14Issue:7Pages:1106-1110
SubtypeArticle
AbstractCurrently, ground-based cloud images taken by using a whole-sky imager are especially popular in the field of meteorology because of their high resolution and accurate cloud information. Cloud images are natural texture images, and thus texture features based on local binary patterns (LBPs) are widely used to analyze texture images. However, the high-computation cost of extracting LBP features from high-resolution cloud texture images may make this technique unacceptable in practical image processing. A commonly adopted method is to resize the original image to an appropriate version with a decreased resolution. But this process will inevitably result in information loss. Accordingly, a measure based on the Kullback-Leibler (KL) divergence of the difference between LBP histogram features extracted from the original and resized images with varying resolutions is reported in this letter. Furthermore, a confidence interval technique is introduced to validate the significance of such difference. Experiments based on real ground-based cloud images show the measurement results of KL divergence in LBP features extracted from original and resized images. The experimental results indicate that images should be resized with caution when performing image processing.
KeywordKullback-leibler (Kl) Divergence Local Binary Patterns (Lbps) Measure Significance
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
WOS KeywordLOCAL BINARY PATTERNS ; TEXTURE CLASSIFICATION ; TROPICAL REGION ; COVER ; SEGMENTATION
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61531019 ; 61601462 ; 61503228)
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000404291500025
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15224
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
3.Shanxi Univ, Sch Software, Taiyuan 030006, Peoples R China
Recommended Citation
GB/T 7714
Wang, Yu,Shi, Cunzhao,Wang, Chunheng,et al. Measure for the Difference Between LBP Features Extracted From Original and Resized Cloud Images With Varying Resolutions[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2017,14(7):1106-1110.
APA Wang, Yu,Shi, Cunzhao,Wang, Chunheng,&Xiao, Baihua.(2017).Measure for the Difference Between LBP Features Extracted From Original and Resized Cloud Images With Varying Resolutions.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,14(7),1106-1110.
MLA Wang, Yu,et al."Measure for the Difference Between LBP Features Extracted From Original and Resized Cloud Images With Varying Resolutions".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 14.7(2017):1106-1110.
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