Laser & Optoelectronics Progress, Volume. 56, Issue 9, 091006(2019)

Enhancement Algorithm of Fractional Differential Medical Images Based on Local Binary Pattern Variance

Hongpu Liu1,2,3, Mengjing Zheng1,3, Xiangdan Hou1,3、*, Bocen Li1,3, and Jiazhuo Du1,3
Author Affiliations
  • 1 School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China
  • 2 School of Electrical Engineering, Hebei University of Technology, Tianjin 300401, China
  • 3 Hebei Provincial Key Laboratory of Big Data Computing, Tianjin 300401, China
  • show less

    The characteristics of fractional differential and its mask operator are investigated, and a new enhancement algorithm of fractional differential images is proposed based on local binary pattern variance (LBPV). The LBPV theory is used for the feature extraction of images. A more effective fractional mask template is constructed. The experimental results show that compared with the existing enhancement algorithms of fractional differential images, the proposed algorithm performs better in the textures and details of enhanced images.

    Tools

    Get Citation

    Copy Citation Text

    Hongpu Liu, Mengjing Zheng, Xiangdan Hou, Bocen Li, Jiazhuo Du. Enhancement Algorithm of Fractional Differential Medical Images Based on Local Binary Pattern Variance[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091006

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Image Processing

    Received: Nov. 7, 2018

    Accepted: Dec. 6, 2018

    Published Online: Jul. 5, 2019

    The Author Email: Hou Xiangdan (hxd@scse.hebut.edu.cn)

    DOI:10.3788/LOP56.091006

    Topics