采用自适应四点窗中点滤波的高椒盐噪声滤除方法

doi:10.11772/j.issn.1001-9081.2017.03.832

计算机应用 ›› 2017, Vol. 37 ›› Issue (3): 832-838.DOI: 10.11772/j.issn.1001-9081.2017.03.832

• 计算机视觉与虚拟现实 • 上一篇下一篇

采用自适应四点窗中点滤波的高椒盐噪声滤除方法

张新明^1,2, 康强¹, 程金凤¹, 涂强¹

1. 河南师范大学计算机与信息工程学院, 河南新乡 453007;
2. 河南省高校计算智能与数据挖掘工程技术研究中心, 河南新乡 453007

收稿日期:2016-09-06 修回日期:2016-11-07 出版日期:2017-03-10 发布日期:2017-03-22
通讯作者: 张新明
作者简介:张新明(1963-),男,湖北孝感人,教授,硕士,CCF会员,主要研究方向:数字图像处理、智能优化算法、模式识别;康强(1989-),男,河南郑州人,硕士研究生,主要研究方向:数字图像处理、智能优化算法;程金凤(1990-),女,河南夏邑人,硕士研究生,主要研究方向:数字图像处理;涂强(1995-),男,河南光山人,硕士研究生,主要研究方向:数字图像处理、智能优化算法。
基金资助:
河南省重点科技攻关项目（132102110209）；河南省基础与前沿技术研究计划项目（142300410295）。

Adaptive four-dot midpoint filter for removing high density salt-and-pepper noise in images

ZHANG Xinming^1,2, KANG Qiang¹, CHENG Jinfeng¹, TU Qiang¹

1. College of Computer and Information Engineering, Henan Normal University, Xinxiang Henan 453007, China;
2. Engineering Technology Research Center for Computing Intelligence & Data Mining of Henan Province, Xinxiang Henan 453007, China

Received:2016-09-06 Revised:2016-11-07 Online:2017-03-10 Published:2017-03-22
Supported by:
This work is partially supported by Technologies R & D Program of Henan Province (132102110209), the Research Program of Basic and advanced technology of Henan Province (142300410295).

摘要/Abstract

摘要： 针对当前中值滤波器处理图像高椒盐噪声效果不佳和实时性不强等问题，提出了一种快速自适应四点窗中点滤波（AFMF）方法。首先，为了降低计算复杂度，使用简单的极值方法检测噪声点；然后，摒弃传统的全点窗口，不用中值滤波，而是在开关滤波和裁剪滤波的基础上，采用新型的非线性滤波方法：中点滤波，简化了算法的流程，提升了算法的计算效率，提高了去噪效果；最后，从3×3窗口开始到由里向外推进，逐渐增大窗口，形成自适应滤波，一直到噪声点处理完，如此避免了窗口大小参数的设置。实验结果表明，与AMF、SAMF、MDBUTMF以及DBCWMF相比，AFMF在处理高密度椒盐噪声上不仅有更好的去噪性能、更快的运行速度（约0.18 s），且无需设置参数，可操作性强，具有较强的实用性。

关键词: 图像恢复, 图像去噪, 开关中值滤波, 自适应滤波, 中点滤波, 四点模板, 椒盐噪声

Abstract: In view of poor denoising performance and unideal speed of the current median filter, a fast and Adaptive Four-dot Midpoint Filter (AFMF) was proposed. Firstly, noise pixels and non-noise pixels of an image were identified using a simple extreme method to reduce the computational complexity. Then, the traditional full-point window was discarded, instead of median filtering, but on the basis of switch filtering and clipping filtering, a new nonlinear filtering method named midpoint filtering was adopted to simplify the algorithm flow, improve the calculation efficiency, improve the denoising effect. Finally, starting from a 3×3 window from inside to outside, the window was gradually enlarged to form adaptive filtering, until all the noise pixels were processed, the setting of window size parameters was avoided. The experimental results show that compared with AMF, SAMF, MDBUTMF and DBCWMF, AFMF not only has better denoising performance but also faster operation speed (about 0.18 s), but also does not need to set parameters, which is easy to operate and has strong practicability.

Key words: image restoration, image denoising, switching median filtering, adaptive filtering, midpoint filtering, four-dot mask, salt-and-pepper noise

中图分类号:

张新明, 康强, 程金凤, 涂强. 采用自适应四点窗中点滤波的高椒盐噪声滤除方法[J]. 计算机应用, 2017, 37(3): 832-838.

ZHANG Xinming, KANG Qiang, CHENG Jinfeng, TU Qiang. Adaptive four-dot midpoint filter for removing high density salt-and-pepper noise in images[J]. Journal of Computer Applications, 2017, 37(3): 832-838.

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采用自适应四点窗中点滤波的高椒盐噪声滤除方法

Adaptive four-dot midpoint filter for removing high density salt-and-pepper noise in images

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