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IEEE transactions on geoscience and remote sensing... 54건

  1. [해외논문]   Hyperspectral Image Classification Using Principal Components-Based Smooth Ordering and Multiple 1-D Interpolation   SCI SCIE

    Ye, Zhijing , Li, Hong , Song, Yalong , Benediktsson, Jon Atli , Tang, Yuan Yan
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1199 - 1209 , 2017 , 0196-2892 ,

    초록

    This paper proposes a spectral-spatial classification algorithm based on principal components (PCs)-based smooth ordering and multiple 1-D interpolation, which can alleviate the general classification problems effectively. Because of the characteristics of hyperspectral image, there always exist easily separable samples (ESSs) and difficultly separable samples (DSSs) in view of the different sets of labeled samples. In this paper, the PC analysis is first used for reducing features and extracting the few first PCs of a hyperspectral image. Then, PC-based smooth ordering is designed for the separation of ESSs and DSSs, and multiple 1-D interpolation is used for the accurate classification of the ESSs. Next, the highly confident samples are selected from the ESSs by the spatial neighborhood information, which are added into the training set for the classification of DSSs. In the case of sufficient training samples, a supervised spectral-spatial method is used for classifying the DSSs by combining the spatial information built with popular extended multiattribute profiles. The proposed algorithm is compared with some state-of-the-art methods on three hyperspectral data sets. The results demonstrate that the presented algorithm achieves much better classification performance in terms of the accuracy and the computation time.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  2. [해외논문]   A Framework of Mixed Sparse Representations for Remote Sensing Images   SCI SCIE

    Li, Feng , Xin, Lei , Guo, Yi , Gao, Junbin , Jia, Xiuping
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1210 - 1221 , 2017 , 0196-2892 ,

    초록

    In this paper, a new framework of mixed sparse representations (MSRs) is proposed for solving ill-conditioned problems with remote sensing images. In general, it is very difficult to find a common sparse representation for remote sensing images because of complicated ground features. Here we regard a remote sensing image as a combination of subimage of smooth, edges, and point-like components, respectively. Since each domain transformation method is capable of representing only a particular kind of ground object or texture, a group of domain transformations are used to sparsely represent each subimage. To demonstrate the effect of the framework of MSR for remote sensing images, MSR is regarded as a prior for maximum a posteriori when solving ill-conditioned problems such as classification and super resolution (SR), respectively. The experimental results show that not only the new framework of MSR can improve classification accuracy but also it can construct a much better high-resolution image than other common SR methods. The proposed framework MSR is a competitive candidate for solving other remote sensing images-related ill-conditioned problems.

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    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  3. [해외논문]   Corrections to “A Combined Rotational Raman-Rayleigh Lidar for Atmospheric Temperature Measurements Over 5–80 km With Self-Calibration” [Dec 16 7055-7065]   SCI SCIE

    Li, Yajuan (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Lin, Xin (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Song, Shalei (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Yang, Yong (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Cheng, Xuewu (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Chen, Zhenwei (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Liu, Linmei (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Xia, Yuan (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ) , Xiong, Jun (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China) , Gong, Shunsheng , Li, Faquan
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1222 - 1222 , 2017 , 0196-2892 ,

    초록

    In the above paper [1] , there are two errors on page 7058. In addition, the support information has been updated to include an additional funding source. The complete funding statement should be:

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

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  4. [해외논문]   Introducing IEEE Collabratec  


    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1223 - 1223 , 2017 , 0196-2892 ,

    초록

    In the above paper [1] , there are two errors on page 7058. In addition, the support information has been updated to include an additional funding source. The complete funding statement should be:

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지

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