A novel spatial approach for classification of high-resolution image scene

In this paper, a novel multi-resolution multi-scale local binary pattern (M2LBP) approach for high-resolution remote sensing image scene classification is presented, characterizing the dominant spatial features in multiple resolution and multiple scale manner. In the proposed M2LBP approach, two different but complementary types of descriptors, the pixel value and radial difference, are utilized to extract both microstructure and macrostructure features from land use and land cover (LULC) classes with high-resolution remote sensing image scene. The proposed approach is extensively validated on two challenging LULC scene datasets and experimental results show that it has superior classification performance over several state-of-the-art classification methods.

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