

FOLLOWUS
College of Electronics and Materials Engineering, Leshan Normal University, Leshan 614000, China
College of Computer Science, Sichuan University, Chengdu 610064, China
Key Lab of Internet Natural Language Processing of Sichuan Provincial Education Department, Leshan Normal University, Leshan 614000, China
Guo HUANG, E-mail: huangguoxuli@163.com
Received:24 December 2019,
Revised:2020-;8-28,
Published:2020-10
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Li XU, Guo HUANG, Qing-li CHEN, et al. An improved method for image denoising based on fractional-order integration[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(10): 1485-1493.
Li XU, Guo HUANG, Qing-li CHEN, et al. An improved method for image denoising based on fractional-order integration[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(10): 1485-1493. DOI: 10.1631/FITEE.1900727.
针对现有图像去噪方法容易造成图像纹理细节丢失的现象,提出一种基于分数积分的去噪新方法。首先,通过拓展柯西积分推导分数阶积分公式,然后利用数值方法估计分数阶积分算子的近似值。最后,在图像8个像素方向构造一个任意阶次的分数阶积分掩模算子。仿真结果表明,本文提出的图像去噪方法在去除噪声的同时,能够保护图像的边缘和纹理信息。并且,由于在迭代过程中采用了纹理保护机制,该方法在去噪后可获得更高的图像特征值和更好的视觉效果。
Given that the existing image denoising methods damage the texture details of an image
a new method based on fractional integration is proposed. First
the fractional-order integral formula is deduced by generalizing the Cauchy integral
and then the approximate value of the fractional-order integral operator is estimated by a numerical method. Finally
a fractional-order integral mask operator of any order is constructed in eight pixel directions of the image. Simulation results show that the proposed image denoising method can protect the edge texture information of the image while removing the noise. Moreover
this method can obtain higher image feature values and better image vision after denoising than the existing denoising methods
because a texture protection mechanism is adopted during the iterative processing.
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