• Journal of Terahertz Science and Electronic Information Technology
  • Vol. 18, Issue 4, 665 (2020)
WANG Chengkai, YANG Xiaomin, and YAN Binyu*
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.11805/tkyda2019139 Cite this Article
    WANG Chengkai, YANG Xiaomin, YAN Binyu. Infrared image super-resolution algorithm based on random forest[J]. Journal of Terahertz Science and Electronic Information Technology , 2020, 18(4): 665 Copy Citation Text show less
    References

    [2] KIMMEL R. Demosaicing: image reconstruction from color CCD samples[J]. IEEE Transactions on Image Processing, 1999, 8(9):1221-1228.

    [3] LI X. Demosaicing by successive approximation[J]. IEEE Transactions on Image Processing, 2005,14(3):370-379.

    [4] SHEN H,ZHANG L,HUANG B,et al. A MAP approach for joint motion estimation,segmentation,and super resolution[J]. IEEE Transactions on Image Processing, 2007,16(2):479-490.

    [5] ZHANG L,ZHANG H,SHEN H,et al. A super-resolution reconstruction algorithm for surveillance images[J]. Signal Processing, 2010,90(3):848-859.

    [6] FARSIU S,ROBINSON M D,ELAD M,et al. Fast and robust multiframe super resolution[J]. IEEE Transactions on Image Processing, 2004,13(10):1327-1344.

    [7] FREEMAN W T,JONES T R,PASZTOR E C. Example-based super-resolution[J]. IEEE Computer Graphics and Applications, 2002,22(2):56-65.

    [8] CHANG H,YEUNG D Y,XIONG Y. Super-resolution through neighbor embedding[C]// Computer Vision and Pattern Recognition. [S.l]:IEEE, 2004,1:I-I.

    [9] ZHANG K,GAO X,LI X,et al. Partially supervised neighbor embedding for example-based image super-resolution[J]. IEEE Journal of Selected Topics in Signal Processing, 2011,5(2):230-239.

    [10] YANG J,WRIGHT J,HUANG T S,et al. Image super-resolution via sparse representation[J]. IEEE Transactions on Image Processing, 2010,19(11):2861-2873.

    [11] ZEYDE R,ELAD M,PROTTER M. On single image scale-up using sparse-representations[C]// International conference on curves and surfaces. Berlin,Heidelberg:Springer, 2010:711-730.

    [13] SCHULTER S,LEISTNER C,BISCHOF H. Fast and accurate image upscaling with super-resolution forests[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Boston,MA,USA:IEEE, 2015:3791-3799.

    [14] YANG X,WU W,LIU K,et al. Fast multisensor infrared image super-resolution scheme with multiple regression models[J]. Journal of Systems Architecture, 2016(64):11-25.

    [15] YANG X,WU W,LIU K,et al. Multi-sensor image super-resolution with fuzzy cluster by using multi-scale and multi-view sparse coding for infrared image[J]. Multimedia Tools and Applications, 2017(76):24871-24902.

    [16] MORRIS N J W,AVIDAN S,MATUSIK W,et al. Statistics of infrared images[C]// Proceedings of Conference on Computervision and Pattern Recognition. Minneapolis,MN:IEEE, 2007:1–7.

    [17] TIMOFTE R,DE V,GOOL V L. Anchored neighborhood regression for fast example-based super-resolution[C]// Proceedings of the IEEE International Conference on Computer Vision. Sydney,NSW:IEEE, 2013:1920-1927.

    WANG Chengkai, YANG Xiaomin, YAN Binyu. Infrared image super-resolution algorithm based on random forest[J]. Journal of Terahertz Science and Electronic Information Technology , 2020, 18(4): 665
    Download Citation