图像去雾算法清晰化效果客观评价方法

郭璠; 蔡自兴

doi:10.3724/SP.J.1004.2012.01410

图像去雾算法清晰化效果客观评价方法

doi: 10.3724/SP.J.1004.2012.01410

郭璠^1,2,
蔡自兴^1,

1.
中南大学信息科学与工程学院长沙 410083;
2.
先进控制与智能自动化湖南省工程实验室长沙 410083

详细信息

通讯作者:
蔡自兴

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- 被引次数: 0
出版历程
- 收稿日期: 2011-10-27
- 修回日期: 2012-03-01
- 刊出日期: 2012-09-20

Objective Assessment Method for the Clearness Effect of Image Defogging Algorithm

GUO Fan^1,2,
CAI Zi-Xing^1
,

1.
School of Information Science and Engineering, Central South University, Changsha 410083;
2.
Hunan Engineering Laboratory for Advanced Control and Intelligent Automation, Changsha 410083

摘要

摘要: 针对目前去雾效果评价方法少和已有评价方法存在局限性等问题, 提出了两种图像清晰化效果评价方法.一种借助由环境渲染或光路传播图所模拟的雾环境图像,采用全参考方式评估算法的去雾效果;一种从人类视觉感知的角度出发,采用无参考方式构建综合评价体系以全面衡量算法的去雾性能.实验证明两种方法均能有效地评价各算法的清晰化效果,且评估结果与人眼的主观感受相一致.本文所提评价方法分别从构建模拟雾环境和人类视觉感知两方面考虑,与已有评价方法相比,在获得全方面评估结论的同时,具有较好的实用性和可靠性.
- 图像去雾算法 /
- 清晰化效果 /
- 图像评价 /
- 模拟雾环境 /
- 人类视觉感知
Abstract: Since there is lack of methodology to assess the performance of defogging algorithm and the existing assessment methods have some limitations, two new methods for assessing the clearness effect of image defogging algorithm are proposed in this paper. One is using synthetic foggy image simulated by environment rendering or transmission map to assess defogging effect in full-reference way. The other is constructing assessment system from the perspective of human visual perception to assess the algorithm performance comprehensively in no-reference way. Experiments show that both methods can assess the effect effectively, and the evaluation results are consistent with our subjective perception. Compared with other existing methods, our proposed methods can assess the effect from the construction of simulated environment and human visual perception, respectively. The new methods can obtain a comprehensive assessment results as well as provide a good practicability and reliability.
- Image defogging algorithm /
- clearness effect /
- image assessment /
- simulated fog environment /
- human visual perception

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