计算机科学 ›› 2018, Vol. 45 ›› Issue (2): 312-317.doi: 10.11896/j.issn.1002-137X.2018.02.054

• 图形图像及模式识别 • 上一篇    下一篇

结合视觉显著性的图像去噪优化算法

赵杰,马玉娇,刘帅奇   

  1. 河北大学电子信息工程学院 河北 保定071000河北省数字医疗工程重点实验室 河北 保定071000,河北大学电子信息工程学院 河北 保定071000河北省数字医疗工程重点实验室 河北 保定071000,河北大学电子信息工程学院 河北 保定071000河北省数字医疗工程重点实验室 河北 保定071000
  • 出版日期:2018-02-15 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金(61572063,61401308),河北大学自然科学研究计划项目(2014-303),河北大学研究生创新资助

Image Denoising Optimization Algorithm Combined with Visual Saliency

ZHAO Jie, MA Yu-jiao and LIU Shuai-qi   

  • Online:2018-02-15 Published:2018-11-13

摘要: 图像在采样、处理、传输及存储过程中受到噪声干扰,导致图像的视觉信息衰退,而人眼对图像中不同区域噪声的敏感程度不同,因此提出了结合视觉显著性的图像去噪优化算法。首先利用视觉显著性对噪声图像进行预处理,得到噪声图像中人眼感兴趣的区域;然后运用对图像纹理保护较好的BM3D算法对该区域进行去噪处理,对非感兴趣的区域采用运算速度较快的算术均值滤波算法实现去噪处理。结果表明,该方法不仅可以获得较高的主观图像质量评价,而且在客观上相比于单纯地使用BM3D算法去噪,运算时间明显缩短。

关键词: 图像去噪,视觉显著性,均值滤波,BM3D算法

Abstract: The image is disturbed by noise in the process of sampling,processing,transmission and storage,which leads to the decline of the visual information of image.Based on the difference of sensitivity of the human eyes to the noise in different regions,this paper put forward an improved image denoising algorithm combined with visual significance.Firstly,the algorithm preprocesses the image by visual significance,and gets the interesting region in the image.Then this paper used the BM3D algorithm,which can better protect the image texture,to denoise this region,and used the arithmetic mean filter algorithm with faster computing speed to denoise the non-interest region.The results show that the proposed method can not only obtain higher subjective image quality evaluation,but also reduce the computational time by using BM3D algorithm.

Key words: Image denoising,Visual salieny,Mean filtering,BM3D algorithm

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