红外图像的动态范围压缩和细节增强
Dynamic Range Compression and Detail Enhancement of Infrared Image
查看参考文献14篇
文摘
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红外图像动态范围压缩和细节增强可有效地提高人眼对图像关键细节信息的获取能力,是红外成像的重要研究课题.针对传统双边滤波器不能最优划分细节层和基础层的问题,设计了区域约束双边滤波器,并提出一种基于该滤波器的红外图像动态范围压缩和细节增强方法.首先通过区域约束双边滤波器将原始红外图像分解为基础层和细节层;然后对基础层进行压缩,对细节层进行增强;最后将这2部分重新合成得到结果图像.实验结果表明,文中设计的滤波器可以更合理地划分图像信息,该方法在压缩图像动态范围的同时可有效地增强不同尺度细节,具有较强的鲁棒性. |
其他语种文摘
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Infrared image dynamic range compression and detail enhancement can effectively improve the human ability of catching information in image's important details. It is an improtant research topic of infrared imaging technology. Because classical bilateral filter can not decompose the original image properly, we design a region-restrained bilateral filter and propose a method on infrared image dynamic range compression and detail enhancement. The method, firstly, decomposes the original infrared image into a base layer and a detail layer by the region-restrained bilateral filter. Secondly, the base layer is compressed and the detail layer is enhanced. Finally, the two parts are recombined and get the result image. The experimental results show that the filter can divide information of the original image more properly. Moreover, the proposed method can robustly compress the dynamic range and effectively enhance the details of different scales. |
来源
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计算机辅助设计与图形学学报
,2014,26(9):1460-1467 【核心库】
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关键词
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红外图像
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动态范围压缩
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细节增强
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地址
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中国科学院沈阳自动化研究所光电信息技术研究室, 中国科学院光电信息处理重点实验室, 沈阳, 110016
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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1003-9775 |
学科
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自动化技术、计算机技术 |
文献收藏号
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CSCD:5255396
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参考文献 共
14
共1页
|
1.
Vickers V E. Plateau equalization algorithm for real-time display of high-quality infrared imagery.
Optical Engineering,1996,35(7):1921-1926
|
被引
32
次
|
|
|
|
2.
宋岩峰. 基于双平台直方图的红外图像增强算法.
红外与激光工程,2008,37(2):308-311
|
被引
29
次
|
|
|
|
3.
毛玉星. 基于空间分布的红外图像直方图均衡算法.
电路与系统学报,2004,9(6):148-151
|
被引
3
次
|
|
|
|
4.
Zuiderveld K. Contrast limited adaptive histogram equalization.
Graphics Gems, vol 4,1994:474-485
|
被引
1
次
|
|
|
|
5.
Branchitta F. Dynamic-range compression and contrast enhancement in infrared imaging systems.
Optical Engineering,2008,47(7):Article No. 076401
|
被引
10
次
|
|
|
|
6.
王巍. 双阈值映射自适应红外图像处理算法.
红外与激光工程,2010,39(6):1184-1187
|
被引
3
次
|
|
|
|
7.
张长江. 红外图像全局和局部对比度增强的非线性增益法.
计算机辅助设计与图形学学报,2006,18(6):844-848
|
被引
4
次
|
|
|
|
8.
Rossi A. Dynamic range reduction and contrast adjustment of infrared images in surveillance scenarios.
Optical Engineering,2013,52(10):Article No. 102002
|
被引
2
次
|
|
|
|
9.
Tumblin J. Lcis: a boundary hierarchy for detail-preserving contrast reduction.
Computer Graphics Proceedings, Annual Conference Series, ACM SIGGRAPH,1999:83-90
|
被引
3
次
|
|
|
|
10.
Branchitta F. New technique for the visualization of high dynamic range infrared images.
Optical Engineering,2009,48(9):Article No. 096401
|
被引
29
次
|
|
|
|
11.
Durand F. Fast bilateral filtering for the display of high -dynamic -range images.
Computer Graphics Proceedings, Annual Conference Series, ACM SIGGRAPH,2002:257-266
|
被引
2
次
|
|
|
|
12.
Zuo C. Display and detail enhancement for high -dynamic -range infrared images.
Optical Engineering,2011,50(12):Article No. 127401
|
被引
1
次
|
|
|
|
13.
Arici T. A histogram modification framework and its application for image contrast enhancement.
IEEE Transactions on Image Processing,2009,18(9):1921-1935
|
被引
56
次
|
|
|
|
14.
Peli E. Contrast in complex images.
Journal of the Optical Society of America A,1990,7(10):2032-2040
|
被引
51
次
|
|
|
|
|