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.

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.

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.

Abstract: A method, a device and a storage medium for extracting height and deformation information of a high voltage transmission tower by using SAR tomography are disclosed. A Spaceborne satellite is used to obtain a plurality of high resolution SAR images of a region having a high voltage transmission tower. The images are then pre-processed via registration, dechirp and phase compensation to obtain observation data. The observation data is then discretized. Then the discretized observation data is resampled by using singular value decomposition, and Akaike information criterion is used to estimate the number of scattering points in the resampled observation data. The obtained number of the scattering points is used to eliminate the singular values in the reconstructed signal. Finally, the sparsity of the observation data is used together with compression sensing to realize signal reconstruction, thereby extracting the height and deformation rate at a position on the high voltage transmission tower.

Abstract: A method, a device and a storage medium for extracting height and deformation information of a high voltage transmission tower by using SAR tomography are disclosed. A Spaceborne satellite is used to obtain a plurality of high resolution SAR images of a region having a high voltage transmission tower. The images are then pre-processed via registration, dechirp and phase compensation to obtain observation data. The observation data is then discretized. Then the discretized observation data is resampled by using singular value decomposition, and Akaike information criterion is used to estimate the number of scattering points in the resampled observation data. The obtained number of the scattering points is used to eliminate the singular values in the reconstructed signal. Finally, the sparsity of the observation data is used together with compression sensing to realize signal reconstruction, thereby extracting the height and deformation rate at a position on the high voltage transmission tower.

Abstract: Techniques for identifying air pollution sources based on aerosol retrieval and a glowworm swarm algorithm are described herein. According to these techniques, a satellite remote sensing image is obtained and a wind speed vector is obtained from the satellite remote sensing image. A GSO algorithm is applied, introducing a glowworm similarity correction factor obtained from an attribute value and a wind speed and wind direction correction factor obtained from the wind speed vector, and pollution sources are identified.

Abstract: The present invention discloses 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.

Abstract: The present invention discloses 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.

Abstract: A method and apparatus for identifying an object are disclosed. The method includes: performing linear feature detection on an image to be identified by using a linear feature detecting method to obtain detected linear features, wherein the linear feature detection method transforms detection of linear features in an image space to detection of extremal points in another space and assigns larger weights to continuous image points than to discrete image points during the transformation by using a continuous cluster factor; and identifying an object to be identified from the detected linear features by considering characteristics of the object to be identified. The method and apparatus for identifying an object of the invention, when used to detect and identify weak linear objects in high resolution remote sensing images, can effectively suppress the system noise and ambient noise, thereby successfully identifying the interested object and avoiding false alarms.

Abstract: The present invention discloses a method for identifying air pollution sources based on aerosol retrieval and a glowworm swarm algorithm.

Abstract: A method and apparatus for identifying an object are disclosed. The method includes: performing linear feature detection on an image to be identified by using a linear feature detecting method to obtain detected linear features, wherein the linear feature detection method transforms detection of linear features in an image space to detection of extremal points in another space and assigns larger weights to continuous image points than to discrete image points during the transformation by using a continuous cluster factor; and identifying an object to be identified from the detected linear features by considering characteristics of the object to be identified. The method and apparatus for identifying an object of the invention, when used to detect and identify weak linear objects in high resolution remote sensing images, can effectively suppress the system noise and ambient noise, thereby successfully identifying the interested object and avoiding false alarms.

Abstract: A method for identifying and extracting a linear object from an image is disclosed. The method comprises: acquiring an original image to be processed, wherein the original image is taken by a camera, received through network transmission or copied from a compact disc or a removable disk; preprocessing the original image to obtain an enhanced image; extracting an edge information image from the enhanced image; then extracting linear features by performing, on the edge information image, a linear feature extracting transform improved with a cluster operator; finally; identifying and extracting the linear object by distinguishing the linear object from other linear features by considering characteristics of the linear object to be identified and extracted.

Abstract: A method for identifying and extracting a linear object from an image is disclosed. The method comprises: acquiring an original image to be processed, wherein the original image is taken by a camera, received through network transmission or copied from a compact disc or a removable disk; preprocessing the original image to obtain an enhanced image; extracting an edge information image from the enhanced image; then extracting linear features by performing, on the edge information image, a linear feature extracting transform improved with a cluster operator; finally; identifying and extracting the linear object by distinguishing the linear object from other linear features by considering characteristics of the linear object to be identified and extracted.