计算机工程

• 图形图像处理 • 上一篇    下一篇

耦合冲击滤波器的片相似性各向异性扩散模型

白云蛟  a,张权  a,尚禹  a,张鹏程  a,刘祎  a,桂志国  a,b   

  1. (中北大学 a.电子测试技术国家重点实验室; b.仪器科学与动态测试教育部重点实验室,太原 030051)
  • 收稿日期:2016-05-04 出版日期:2017-03-15 发布日期:2017-03-15
  • 作者简介:白云蛟(1990—),男,博士研究生,主研方向为图像处理;张权,副教授、博士;尚禹,教授、博士;张鹏程、刘祎,讲师、博士;桂志国(通信作者),教授、博士生导师。
  • 基金项目:
    国家自然科学基金(61271357);国家重大科学仪器设备开发专项(2014YQ240445);山西省自然科学基金(2015011046);北京理工大学爆炸科学与技术国家重点实验室开放课题(KFJJ13-11M)。

Patch Similarity Based Anisotropic Diffusion Model Coupled with Shock Filter

BAI Yunjiao  a,ZHANG Quan  a,SHANG Yu  a,ZHANG Pengcheng  a,LIU Yi  a,GUI Zhiguo  a,b   

  1. (a.National Key Laboratory for Electronic Measurement Technology; b.Key Laboratory of Instrumentation Science & Dynamic Measurement of Ministry of Education,North University of China,Taiyuan 030051,China)
  • Received:2016-05-04 Online:2017-03-15 Published:2017-03-15

摘要: 在图像去噪过程中,为保持图像边缘并去除噪声,提出一种结合片相似性各向异性扩散(AD)和冲击滤波器的图像去噪和增强模型。采用片相似性AD模型去除图像中的噪声,引入冲击滤波器增强图像的重要结构特征。构造关于图像梯度模的函数,并自适应地调节图像在同质区域、细节和边缘区域的增强系数,在增强图像细节的同时,抑制噪声的放大和过冲现象。实验结果表明,该模型在视觉效果和客观评价指标方面均优于传统的AD模型、片相似性AD模型、结合冲击滤波器的AD模型,不仅能有效地去除噪声,且更好地保留了图像的细节和边缘特征。

关键词: 片相似性, 冲击滤波器, 各向异性扩散, 增强系数, 图像去噪, 图像增强

Abstract: In order to preserve edge and remove noise during the image denosing,a model combining the patch similarity based Anisotropic Diffusion(AD) and the shock filter is proposed for image denoising and enhancement.The proposed model makes use of the patch similarity based AD model to remove noise and introduces the shock filter to enhance the important structure features of the image.The function with respect to the modulus of the image gradient is constructed to adaptively adjust the enhancement coefficients in the homogenous region,detail and edge region of the image.This function suppresses the noise amplification and the overshoot phenomenon when the proposed model enhances the details of the image.Experimental results show that the proposed model,which is superior to the traditional AD model,patch similarity based AD model and shock filter combined AD model in the aspects of visual effects and objective evaluation indexes,can not only effectively remove noise,but also better preserve the detail and edge features of the image.

Key words: patch similarity, shock filter, Anisotropic Diffusion(AD), enhancement coefficient, image denoising, image enhancement

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