Image Enhancement Algorithm Based on Dual Domain Decomposition

doi:10.3969/j.issn.0372-2112.2020.07.009

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Image Enhancement Algorithm Based on Dual Domain Decomposition

更新时间：2025-07-08

- Image Enhancement Algorithm Based on Dual Domain Decomposition
- Acta Electronica Sinica Vol. 48, Issue 7, Pages: 1311-1320(2020)
- 作者机构：
  
  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
  6. 兖矿集团信息化管理中心山东邹城,273500
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.51674269);Key Subject of Beijing Polytechnic College (No.BGZYKY201855Z)
- DOI：10.3969/j.issn.0372-2112.2020.07.009
  CLC： TP391.1
- Published Online：25 July 2020，
  
  Published：2020
- 稿件说明：
移动端阅览
Image Enhancement Algorithm Based on Dual Domain Decomposition[J]. Acta Electronica Sinica, 2020, 48(7): 1311-1320.
DOI：

Image Enhancement Algorithm Based on Dual Domain Decomposition[J]. Acta Electronica Sinica, 2020, 48(7): 1311-1320. DOI： 10.3969/j.issn.0372-2112.2020.07.009.

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.

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.

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