Atmospheric aerosol inversion based on statistical and OTSU segmentation

    公开(公告)号:US11733175B2

    公开(公告)日:2023-08-22

    申请号:US17489300

    申请日:2021-09-29

    CPC classification number: G01N21/94 G01N21/3504

    Abstract: Embodiments include a method for retrieving atmospheric aerosol based on statistical segmentation. Firstly a multi-band remote sensing image including an apparent reflectance and an aerosol optical thickness look-up table corresponding to a retrieval band is obtained, then pixels are partitioned and screened according to apparent reflectance segments of a mid-infrared 2.1 micrometer band. After that the retained pixel sets are further partitioned and screened according to the apparent reflectance segments of the mid-infrared 1.6 micrometer band. Finally the obtained pixel sets are partitioned into two categories according to the pixel number, one category including pixels having more pixels, the other including those with less pixels. The category with more pixels is taken as the reference part for retrieval.

    ATMOSPHERIC AEROSOL INVERSION BASED ON STATISTICAL AND OTSU SEGMENTATION

    公开(公告)号:US20220018787A1

    公开(公告)日:2022-01-20

    申请号:US17489300

    申请日:2021-09-29

    Abstract: Embodiments include a method for retrieving atmospheric aerosol based on statistical segmentation. Firstly a multi-band remote sensing image including an apparent reflectance and an aerosol optical thickness look-up table corresponding to a retrieval band is obtained, then pixels are partitioned and screened according to apparent reflectance segments of a mid-infrared 2.1 micrometer band. After that the retained pixel sets are further partitioned and screened according to the apparent reflectance segments of the mid-infrared 1.6 micrometer band. Finally the obtained pixel sets are partitioned into two categories according to the pixel number, one category including pixels having more pixels, the other including those with less pixels. The category with more pixels is taken as the reference part for retrieval.

    METHOD FOR RETRIEVING ATMOSPHERIC AEROSOL BASED ON STATISTICAL SEGMENTATION

    公开(公告)号:US20210318253A1

    公开(公告)日:2021-10-14

    申请号:US16885021

    申请日:2020-05-27

    Abstract: Embodiments include a method for retrieving atmospheric aerosol based on statistical segmentation. Firstly a multi-band remote sensing image including an apparent reflectance and an aerosol optical thickness look-up table corresponding to a retrieval band is obtained, then pixels are partitioned and screened according to apparent reflectance segments of a mid-infrared 2.1 micrometer band. After that the retained pixel sets are further partitioned and screened according to the apparent reflectance segments of the mid-infrared 1.6 micrometer band. Finally the obtained pixel sets are partitioned into two categories according to the pixel number, one category including pixels having more pixels, the other including those with less pixels. The category with more pixels is taken as the reference part for retrieval.

    Ground-based interferometric synthetic aperture radar-based atmospheric phase compensation method

    公开(公告)号:US10705205B2

    公开(公告)日:2020-07-07

    申请号:US16012791

    申请日:2018-06-20

    Abstract: The present invention relates to the technical field of synthetic aperture radar, and in particular to a ground-based interference synthetic aperture radar-based atmospheric phase compensation method. The present invention first uses the inverse fast Fourier transform algorithm to rapidly and effectively realize the focusing in the range and cross-range dimension. Then a triple threshold method which combines coherence coefficient, amplitude, and amplitude dispersion index is used to select reliable PS points. Finally, under a full consideration of the spatial correlation of the atmospheric phase, the atmospheric phase is estimated by using a two-dimensional-polynomial model. The present invention can rapidly and accurately estimate and compensate the atmospheric phase, is helpful in improving the accuracy of GB-InSAR real-time measurement, and valuable and universal in practical application.

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