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  • Open Access


    Remote Sensing Image Retrieval Based on 3D-Local Ternary Pattern (LTP) Features and Non-subsampled Shearlet Transform (NSST) Domain Statistical Features

    Hilly Gohain Baruah*, Vijay Kumar Nath, Deepika Hazarika

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 137-164, 2022, DOI:10.32604/cmes.2022.018339

    Abstract With the increasing popularity of high-resolution remote sensing images, the remote sensing image retrieval (RSIR) has always been a topic of major issue. A combined, global non-subsampled shearlet transform (NSST)-domain statistical features (NSSTds) and local three dimensional local ternary pattern (3D-LTP) features, is proposed for high-resolution remote sensing images. We model the NSST image coefficients of detail subbands using 2-state laplacian mixture (LM) distribution and its three parameters are estimated using Expectation-Maximization (EM) algorithm. We also calculate the statistical parameters such as subband kurtosis and skewness from detail subbands along with mean and standard deviation calculated from approximation subband, and… More >

  • Open Access


    An Efficient Detection Approach of Content Aware Image Resizing

    Ming Lu1, 2, *, Shaozhang Niu1, Zhenguang Gao3

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 887-907, 2020, DOI:10.32604/cmc.2020.09770

    Abstract Content aware image resizing (CAIR) is an excellent technology used widely for image retarget. It can also be used to tamper with images and bring the trust crisis of image content to the public. Once an image is processed by CAIR, the correlation of local neighborhood pixels will be destructive. Although local binary patterns (LBP) can effectively describe the local texture, it however cannot describe the magnitude information of local neighborhood pixels and is also vulnerable to noise. Therefore, to deal with the detection of CAIR, a novel forensic method based on improved local ternary patterns (ILTP) feature and gradient… More >

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