基于地物波谱特性的透射率-暗原色先验去雾增强算法

史德飞; 李勃; 丁文; 陈启美

doi:10.3724/SP.J.1004.2013.02064

基于地物波谱特性的透射率-暗原色先验去雾增强算法

doi: 10.3724/SP.J.1004.2013.02064

1.
南京大学电子科学与工程学院南京 210046

基金项目:

国家自然科学基金（61105015），江苏省自然科学基金（BK2011511），江苏省科技支撑计划（BE2011747）资助

详细信息

作者简介:
史德飞南京大学电子科学与工程学院硕士研究生. 主要研究方向为图像处理.E-mail：st_fly@sina.com

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出版历程
- 收稿日期: 2012-08-03
- 修回日期: 2012-09-29
- 刊出日期: 2013-12-20

Haze Removal and Enhancement Using Transmittance-dark Channel Prior Based on Object Spectral Characteristic

1.
School of Electronic Science and Engineering, Nanjing University, Nanjing 210046

Funds:

Supported by National Natural Science Foundation of China (61105015), Natural Science Foundation of Jiangsu Province (BK2011511), and Science and Technology Support Program of Jiangsu Province (BE2011747)

摘要

摘要: 室外场景在雾、霾等天气的影响下能见度降低、成像效果不佳. 本文从大气散射成像模型出发，从地物波谱特性的角度拓展暗原色先验理论，进而根据人眼视锥细胞对短中长波长光的刺激比例（LMS）将RGB 三通道转换为耦合性更低的透射率三通道，有效地降低了RGB三通道间的互相关性，并在对数图像处理（Logarithmic image processing，LIP）的框架下，提出基于彩色对数图像处理模型的自适应增强算法，对去雾后的图像进行增强. 实验结果表明，耦合性更低的透射率三通道可以更准确地复原出图像，同时采用基于彩色对数图像处理模型的增强算法可以明显地提高图像的可视性.
- 去雾 /
- 地物波谱特性 /
- LMS /
- 暗原色先验 /
- 彩色对数图像处理
Abstract: Images of outdoor scenes are usually degraded because of haze, fog and so on. Considering the atmospheric SCAttering model and object spectral characteristic, we expand dark channel prior and compute the transmittance channels in the LMS model to reduce corrections between RGB channels, and we also propose an adaptive LIPC algorithm to enhance the haze removal images based on logarithmic image processing (LIP). Results show that dark channel prior acts better in the transmittance channels than in RGB channels because of its lower correction with each other, and that haze removal images enhanced with LIPC are more credible and acceptable.
- Image haze removal /
- object spectral characteristic /
- LMS /
- dark channel prior /
- LIPC

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参考文献(13)

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