• DocumentCode
    232802
  • Title

    An adaptive regularization image super-resolution reconstruction algorithm

  • Author

    Zhao Xiao-qiang ; Jia Yun-xia

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Tech., Lanzhou, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    7258
  • Lastpage
    7262
  • Abstract
    Because of the traditional regularization parameters in the regularization method is fixed, in reconstruction images are not good to keep details such as image edge and texture information.In view of these shortcomings is proposed in this paper a bilateral total variation based on adaptive regularization image super-resolution algorithm, through changing regularized parameter to control the data fidelity term in the objective function and the proportion of regularization.Experimental results show that compared with the traditional reconstruction method in this paper, the method to the determination of adaptive regularization parameter, find the optimal solution, and in the region of the edge and texture details such as embodies better reconstruction effect.
  • Keywords
    image reconstruction; image resolution; image texture; adaptive regularization image; adaptive regularization parameter; bilateral total variation; data fidelity term; image edge information; image super-resolution reconstruction algorithm; image texture information; objective function; reconstruction effect; regularization method; regularization parameters; Electronic mail; Image edge detection; Image reconstruction; Image resolution; Image restoration; Reconstruction algorithms; TV; adaptive regularization; bilateral total variational; super-resolution reconstruction; to keep edge;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2014 33rd Chinese
  • Conference_Location
    Nanjing
  • Type

    conf

  • DOI
    10.1109/ChiCC.2014.6896202
  • Filename
    6896202