基于变分模型的梯度域色阶映射算法

席志红; 赵蓝飞; 张驰; 张志民

doi:10.11959/j.issn.1000-436x.2015001

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基于变分模型的梯度域色阶映射算法

学术论文 | 更新时间：2024-06-05

- 基于变分模型的梯度域色阶映射算法
- Tone mapping based on variational model in gradient domain
- 通信学报 2015年36卷第1期页码：1-8
- 作者机构：
  
  哈尔滨工程大学信息与通信工程学院，黑龙江哈尔滨 150001
- 作者简介：
  
  [ "席志红（1965-），女，黑龙江哈尔滨人，博士，哈尔滨工程大学教授，主要研究方向为数字图像处理、嵌入式系统设计、信号与信息处理等。" ]
  [ "赵蓝飞[通信作者]（1985-），男，满族，黑龙江哈尔滨人，哈尔滨工程大学博士生，主要研究方向为数字图像处理、嵌入式系统设计、模式识别等。E-mail:zlf82563144@163.com。" ]
  [ "张驰（1978-），男，黑龙江哈尔滨人，硕士，哈尔滨工程大学讲师，主要研究方向为电路系统、现代数字通信系统、数字信号处理。" ]
  [ "张忠民（1972-），男，回族，黑龙江克东人，哈尔滨工程大学副教授，主要研究方向为模式识别、嵌入式系统设计、电路系统。" ]
- 基金信息：
  
  国家自然科学基金资助项目(60875025)
- DOI：10.11959/j.issn.1000-436x.2015001
  中图分类号： TP391.41
- 网络出版日期：2015-01，
  
  纸质出版日期：2015-01-25
- 稿件说明：
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席志红, 赵蓝飞, 张驰, 等. 基于变分模型的梯度域色阶映射算法[J]. 通信学报, 2015,36(1):1-8.

IZhi-hong X, Lan-fei ZHAO, Chi ZHANG, et al. Tone mapping based on variational model in gradient domain[J]. Journal on communications, 2015, 36(1): 1-8.
席志红, 赵蓝飞, 张驰, 等. 基于变分模型的梯度域色阶映射算法[J]. 通信学报, 2015,36(1):1-8. DOI： 10.11959/j.issn.1000-436x.2015001.

IZhi-hong X, Lan-fei ZHAO, Chi ZHANG, et al. Tone mapping based on variational model in gradient domain[J]. Journal on communications, 2015, 36(1): 1-8. DOI： 10.11959/j.issn.1000-436x.2015001.

摘要

针对梯度域动态范围压缩算法存在伪边缘以及局部细节扭曲等现象，提出了一种基于变分模型的梯度域色阶映射方法。首先，在梯度域内构造了一个既能够压缩图像的动态范围又能够保证边缘与细节信息的变分模型；其次，将Gibbs采样的思想引入到最速下降法中，在求解变分模型最优解的同时有效地提高了无约束最优算法的收敛速度；最后通过改进的最速下降法得到变分模型最优解。实验结果表明该算法能够有效地去除光晕，得到细节保持完好的低动态范围图像。另外，改进的最速下降法保证了算法的实时性。

Abstract

Due to the low dynamic range image which was generated by the gradient domain high dynamic range compression algorithm contain the artificial boundaries and local detail distortions

a variational model in gradient domain was proposed to improve the performance of the traditional algorithm.First of all

a variational model in gradient domain was introduced to compress dynamic range

meanwhile details and edges were preserved simultaneously.Afterwards

the rate of convergence was improved by introducing the ideology of Gibbs sampler.Eventually

the improved method was employed to obtain the optimal solution of the variational model.Experimental results demonstrate that proposed algorithm reduces the degree of artificial boundaries

meanwhile low dynamic range image represents excellent capacity of detail preservation.Moreover

the real-time performance is guaranteed by the improved steepest descent method.

关键词

Keywords

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