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

Hongpu Liu; Mengjing Zheng; Xiangdan Hou; Bocen Li; Jiazhuo Du

doi:10.3788/LOP56.091006

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 9 >Page 091006 > Article

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

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

Hongpu Liu^1,2,3, Mengjing Zheng^1,3, Xiangdan Hou^1,3,*, Bocen Li^1,3, and Jiazhuo Du^1,3

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

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DOI: 10.3788/LOP56.091006 Cite this Article Set citation alerts

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 Copy Citation Text

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Abstract

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.

Keywords

fractional differential image enhancement image processing local binary pattern variance mask operator