[1]马宁,周则明,张鹏,等.基于视觉感知与梯度域的遥感图像对比度增强变分模型[J].东南大学学报(自然科学版),2015,45(6):1051-1056.[doi:10.3969/j.issn.1001-0505.2015.06.005]
 Ma Ning,Zhou Zeming,Zhang Peng,et al.Variational model for contrast enhancement of remote sensing images based on perception and gradient domain[J].Journal of Southeast University (Natural Science Edition),2015,45(6):1051-1056.[doi:10.3969/j.issn.1001-0505.2015.06.005]
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基于视觉感知与梯度域的遥感图像对比度增强变分模型()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
45
期数:
2015年第6期
页码:
1051-1056
栏目:
计算机科学与工程
出版日期:
2015-11-20

文章信息/Info

Title:
Variational model for contrast enhancement of remote sensing images based on perception and gradient domain
作者:
马宁12周则明1张鹏1罗立民2
1解放军理工大学气象海洋学院, 南京 211101; 2东南大学计算机科学与工程学院, 南京 210096
Author(s):
Ma Ning12 Zhou Zeming1 Zhang Peng1 Luo Limin2
1 College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China
2 School of Computer Science and Engineering, Southeast University, Nanjing 210096, China
关键词:
视觉感知 梯度域 变分 对比度增强
Keywords:
perception gradient domain variational contrast enhancement
分类号:
TP391.4
DOI:
10.3969/j.issn.1001-0505.2015.06.005
摘要:
基于视觉感知增强变分模型与梯度域增强变分模型,提出了一种新的遥感图像对比度增强变分模型.首先,定义梯度增强项为一个高斯增强函数,该函数利用高斯滤波器对图像进行预处理,以克服梯度对噪声敏感的不足,并根据图像中各点梯度信息自适应地选择保持或者放大原图像的梯度信息.然后,将梯度增强项引入到视觉感知增强模型中,以提高图像对比度并保持更多细节信息.最后,利用梯度下降流法最小化模型的能量泛函并采用数值化方法获取最优解.从全局和局部对比度增强两个方面验证了所提模型的有效性.实验结果表明,相对于现有其他增强变分模型,局部对比度增强模型能够取得更好的主观视觉效果和客观性能评价指标.
Abstract:
A novel variational model for contrast enhancement of remote sensing images is proposed based on the perceptual-based variational model and the gradient-based variational model. First, the Gaussian enhancement function is designed for the gradient enhancement term. This function uses the Gaussian filter to preprocess the image to overcome the shortage that the gradient is sensitive to noise, and it can keep or enhance the gradient information adaptively according to the gradient information of the source image. Then, the gradient enhancement term is introduced into the perceptual-based enhancement model to improve the contrast and preserve more detail information of the source image. Finally, the gradient descent flow method is applied to minimize the energy functional and the numerical scheme is used to acquire the optimization solution. The effectiveness of the proposed model is verified from global and local contrast enhancement. The experimental results show that compared with other existing variational enhancement models, the local contrast enhancement model can achieve better subjective visual effect and objective performance evaluation.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2015-04-21.
作者简介: 马宁(1977—),男,博士,讲师,flywithyu@aliyun.com.
引用本文: 马宁,周则明,张鹏,等.基于视觉感知与梯度域的遥感图像对比度增强变分模型[J].东南大学学报:自然科学版,2015,45(6):1051-1056. [doi:10.3969/j.issn.1001-0505.2015.06.005]
更新日期/Last Update: 2015-11-20