自适应窗口形状的中值滤波

邹永宁; 姚功杰

doi:10.3788/OPE.20182612.3028

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自适应窗口形状的中值滤波

信息科学 | 更新时间：2020-07-05

- 自适应窗口形状的中值滤波
- Median filtering algorithm for adaptive window shape
- 光学精密工程 2018年26卷第12期页码：3028-3039
- 作者机构：
  
  1.重庆大学光电技术及系统教育部重点实验室ICT研究中心, 重庆 400044
  2.重庆大学光电工程学院, 重庆 400044
- 作者简介：
  
  [ "邹永宁(1974-), 男, 江西乐安人, 副研究员, 硕士生导师, 博士, 主要从事CT图像重建、CT体数据可视化、图像并行处理方面的研究。E-mail:zynlxu@sina.com" ]
  [ "姚功杰(1995-), 男, 福建平潭人, 硕士研究生, 2017年于河南科技大学获得学士学位, 主要从事工业CT, 图像处理的研究。E-mail:617823648@qq.com" ]
- 基金信息：
  
  国家重大科学仪器设备开发专项(2013YQ030629)
- DOI：10.3788/OPE.20182612.3028
  中图分类号： TH703
- 收稿日期：2018-05-29，
  
  录用日期：2018-7-14，
  
  纸质出版日期：2018-12-25
- 稿件说明：
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邹永宁, 姚功杰. 自适应窗口形状的中值滤波[J]. 光学精密工程, 2018,26(12):3028-3039.

Yong-ning ZOU, Gong-jie YAO. Median filtering algorithm for adaptive window shape[J]. Optics and precision engineering, 2018, 26(12): 3028-3039.
邹永宁, 姚功杰. 自适应窗口形状的中值滤波[J]. 光学精密工程, 2018,26(12):3028-3039. DOI： 10.3788/OPE.20182612.3028.

Yong-ning ZOU, Gong-jie YAO. Median filtering algorithm for adaptive window shape[J]. Optics and precision engineering, 2018, 26(12): 3028-3039. DOI： 10.3788/OPE.20182612.3028.

摘要

中值滤波去除噪声的同时，难免出现含有线形图像的边缘轮廓信息跟随丢失的情况。为了达到滤除图像噪声最大化，有用信息损失最小化的目的，根据图像边缘特征选择或设计了适当大小和形状的窗口来进行中值滤波等操作。一方面，创新性地提出将Hough变换应用到车轮裂缝CT图像的滤波窗口形状的选择上，针对单一方向轮廓的图像，利用Hough变换检测出裂缝的方向，从而采用与裂缝形状相应的窗口对裂缝进行有针对性滤波，将该方法与传统方法进行了对比实验，并将60层滤波后切片图像堆栈得到了三维图像；另一方面，针对含有多个方向轮廓的图像，为了进一步改善滤波效果，提出根据像素梯度设计斜向滤波器，对多方向的线对进行滤波，数据显示经改进方法滤波后图像的峰值信噪比（PSNR）较传统的中值滤波提高了4~6，结构相似性（SSIM）提高了1%~2%左右，最后用683层荞麦切片CT图堆栈得到三维图像，对比滤波前后图像，可知该方法滤波效果良好。

Abstract

While removing noise

the loss of useful information is inevitable

especially the edge information of linear images. To maximize the image and minimize the loss of useful information according to the edge features of the testing image

a window with appropriate size and shape was selected to perform median filtering and other operations. It is innovatively proposed to apply a Hough transform to the filtering window shape selection of the wheel crack CT image

aiming at the image of the single direction contour. The Hough transform was used to detect the direction of the contour

and the corresponding shape window was used to filter the crack. This method was compared with the traditional method

and the image with better visual effect can be obtained after pre-processing by Hough transform. In this paper

to improve the filtering effect for images with multi-direction edge contours

an oblique filter is designed according to the pixel gradient. The data shows that the peak signal-to-noise ratio (PSNR) of the image after proposed filtering is improved by 4-6 compared with the traditional median filter. The structure similarity (SSIM) is increased by approximately 1%-2%. Three-dimensional images are obtained using the stack of CT images of buckwheat slices. The filtering result of the proposed method is favorable by the contrast of before and after.

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references

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