LWIR image visualization preserving local details and global distribution by gradient-domain image reconstruction.

机译：LWIR图像可视化通过梯度域图像重建来保留局部细节和全局分布。

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摘要

Recent developments of long wave infrared (LWIR) devices and LWIR sensor technologies enable us to obtain an LWIR image with high bit depth and low signal-noise ratio. To exploit these recent developments, we propose a novel temperature visualization method that can simultaneously represent global distribution and local details of the input temperature. The global temperature distribution is represented by pseudo color. On the other hand, to manipulate the local temperature details, the output luminance is generated by gradient-domain image reconstruction. Experimental results on real LWIR images show the effectiveness of the proposed method.

机译：长波红外（LWIR）设备和LWIR传感器技术的最新发展使我们可以获得具有高位深度和低信噪比的LWIR图像。为了利用这些最新发展，我们提出了一种新颖的温度可视化方法，该方法可以同时表示输入温度的全局分布和局部细节。全局温度分布由伪色表示。另一方面，为了操纵局部温度细节，通过梯度域图像重建来产生输出亮度。在真实的LWIR图像上的实验结果表明了该方法的有效性。

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来源
《Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVIII》|2017年|101780X.1-101780X.11|共11页
会议地点 Anaheim(US)
作者
Takashi Shibata; Masayuki Tanaka; Masatoshi Okutomi;
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作者单位

NEC Corporation, Kanagawa, Japan,Tokyo Institute of Technology, Tokyo, Japan;

Tokyo Institute of Technology, Tokyo, Japan;

Tokyo Institute of Technology, Tokyo, Japan;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
long wave infrared (LWIR); gradient domain image reconstruction; detail enhancement; image expression;

机译：长波红外（LWIR）;梯度域图像重建；细节增强；图像表达;

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专利

1. Enhanced local tone mapping for detail preserving reproduction of high dynamic range images [J] . El Mezeni Dragomir M., Saranovac Lazar V. Journal of visual communication & image representation . 2018,第MAY期

机译：增强的本地色调映射，用于保留细节，以保留高动态范围图像的再现
2. High dynamic range infrared images detail enhancement based on local edge preserving filter [J] . Song Qiong, Wang Yuehuan, Bai Kun Infrared physics and technology . 2016,第Null期

机译：基于局部边缘保留滤镜的高动态范围红外图像细节增强
3. Visualizing Web Images Using Fisher Discriminant Locality Preserving Canonical Correlation Analysis [J] . Kohei TATENO, Takahiro OGAWA, Miki HASEYAMA IEICE transactions on information and systems . 2017,第9期

机译：使用Fisher判别式局部化保持规范相关分析的可视化Web图像
4. LWIR image visualization preserving local details and global distribution by gradient-domain image reconstruction. [C] . Takashi Shibata, Masayuki Tanaka, Masatoshi Okutomi Conference on Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVIII . 2017

机译：LWIR图像可视化保留梯度域图像重建的本地细节和全局分布。
5. Local, Non-local and Global Methods in Image Reconstruction. [D] . Lou, Yifei. 2010

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LWIR image visualization preserving local details and global distribution by gradient-domain image reconstruction.

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