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- W1996467853 abstract "This paper we selected 5 typical texture class samples from Quick Bird RGB fused data with 0.61m resolution. We used GLCMs to quantitatively calculate texture features, which parameter values are suitable for the specific texture classifications. Six statistical features for every class sample in four orientations and 1 pixel of pair-wise distance were obtained, including: energy, entropy, contrast, homogeneity, correlation, and dissimilarity respectively. The average values in four directions were computed and compared. The results show that dissimilarity and entropy have biggest value differences among six samples. They are the most important features for classification or recognition of class samples. The statistics of dissimilarity, entropy, homogeneity, contrast have been demonstrated a decrease in classification ability. The results of the research supplied important references for the quantitative interpretation of VHR Quick Bird imagery in the applications of land cover/use classification and mapping." @default.
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- W1996467853 date "2012-05-01" @default.
- W1996467853 modified "2023-09-27" @default.
- W1996467853 title "Statistical Class Feature in Texture Analysis of Remote Sensing Imagery" @default.
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- W1996467853 doi "https://doi.org/10.4028/www.scientific.net/amr.518-523.5749" @default.
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