电子学报 ›› 2020, Vol. 48 ›› Issue (7): 1311-1320.DOI: 10.3969/j.issn.0372-2112.2020.07.009

• 学术论文 • 上一篇    下一篇

基于双域分解的图像增强算法

田子建1, 王满利1,2, 张元刚3   

  1. 1. 中国矿业大学(北京)机电与信息工程学院, 北京 100083;
    2. 河南理工大学物理与 电子信息学院, 河南焦作 454000;
    3. 兖矿集团信息化管理中心, 山东邹城 273500
  • 收稿日期:2019-01-18 修回日期:2019-11-22 出版日期:2020-07-25 发布日期:2020-07-25
  • 通讯作者: 田子建
  • 作者简介:王满利 男,1981年出生,河南焦作人.中国矿业大学(北京)机电与信息工程学院信息与通信专业博士研究生,主要研究方向为图像处理.E-mail:wml920@163.com
  • 基金资助:
    国家自然科学基金(No.51674269);北京工业职业技术学院重点课题(No.BGZYKY201855Z)

Image Enhancement Algorithm Based on Dual Domain Decomposition

TIAN Zi-jian1, WANG Man-li1,2, ZHANG Yuan-gang3   

  1. 1. School of Mechanical Electronic & Information Engineering, China University of Mining & Technology, Beijing 100083, China;
    2. School of Physics & Electronic Information Engineering, HeNan Polytechnic University, Jiaozuo, Henan 454000, China;
    3. Information Center of YanKuang Group, Zoucheng, Shandong 273500, China
  • Received:2019-01-18 Revised:2019-11-22 Online:2020-07-25 Published:2020-07-25

摘要: 为解决图像增强中对比度提高与噪声抑制的矛盾,本文提出了一种基于双域分解的图像增强算法,同步实现图像对比度提高与噪声抑制.文中详述了空域分解、分层图像空域增强与变换域降噪、分层图像合成三个主要环节的原理、方法.首先,高斯滤波器将图像分解为基础层和细节层,实现对比度提高与噪声抑制的解耦合;其次,带校正功能的单尺度Retinex和硬阈值收缩的非下采样剪切波降噪算法同步实现基础层的增强和细节层的降噪;最后,分层图像合成、灰度数值延展和微分算子强化,实现合成图像的灰度延展与细节加强,确保增强图像的颜色均匀、细节突出.实验表明,本文算法提高图像对比度和抑制噪声的性能优于其他九种算法.

关键词: 图像增强, 空域分解, 高斯滤波器, 单尺度Retinex, 非下采样剪切波变换

Abstract: To solve the contradiction between contrast enhancement and noise suppression in image enhancement,an image enhancement algorithm based on dual domain decomposition (IEDD) is proposed.The principles and methods including spatial domain decomposition,layered spatial images enhancement and transform domain noise reduction,and layered images synthesis are described in detail.Firstly,the image is decomposed into a base layer and a detail layer by a Gaussian filter,that decouples the contrast enhancement and noise reduction.Next,in order to realize the enhancement of base layer and noise reduction of detail layers synchronously,the single-scale Retinex with correction function and the nonsubsampled shearlet denoising algorithm with hard threshold shrinkage are implemented.Finally,to ensure the uniform color and the outstanding detail of the composite image,layered image fusion,gray value extension and differential operator detail enhancement are implemented,realizing the grayscale extension and detail enhancement of the composite image.Experiments show that the performance of the proposed algorithm is better than other nine algorithms in improving image contrast and suppressing noise.

Key words: image enhancement, spatial decomposition, Gaussian filter, single scale Retinex, non-subsampled shearlet transform

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