Tone mapping based on variational model in gradient domain

IZhi-hong X; Lan-fei ZHAO; Chi ZHANG; Zhong-min ZHANG

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

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Tone mapping based on variational model in gradient domain

Academic paper | 更新时间：2024-06-05

- Tone mapping based on variational model in gradient domain
- Journal on Communications Vol. 36, Issue 1, Pages: 1-8(2015)
- 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：
- 基金信息：
  
  The National Natural Science Foundation of China(60875025)
- DOI：10.11959/j.issn.1000-436x.2015001
  CLC： TP391.41
- Online First：2015-01，
  
  Published：25 January 2015
- 稿件说明：
移动端阅览
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：

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.

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references

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