Image fusion of the Terahertz-visual NAECON Grand Challenge data
Image fusion of the Terahertz-visual NAECON Grand Challenge data
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DOI：
10.1109/naecon.2012.6531058
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发表时间：
2012-07
期刊：
影响因子：
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通讯作者：
Erik Blasch;Zheng Liu;D. Petkie;R. Ewing;G. Pomrenke;K. Reinhardt
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作者：
Erik Blasch;Zheng Liu;D. Petkie;R. Ewing;G. Pomrenke;K. Reinhardt
过去三十年来，太赫兹 (THz) 传感技术在隐蔽武器探测、医学成像和无损评估方面得到了发展；然而，太赫兹图像利用的方法尚未得到很好的报道。我们为 2011 年 IEEE 国家航空航天和电子会议测试了多尺度图像融合算法。 (NAECON) Grand Challenge，由太赫兹 (THz) 和视觉图像组成。该研究包括图像表征（信号分布）、图像处理（数据融合）和图像分析（边缘检测）。我们发现太赫兹图像表征不一定遵循明显的高斯分布，太赫兹图像与视觉数据的融合支持目标检测，并且图像分析增强了目标评估。对于初始实验，我们通过边缘检测、图像融合结果和图像融合质量评估来评估目标分割。初步的图像开发和融合结果可以进一步开发服装遮挡隐蔽武器成像的太赫兹采集、参数优化和目标评估。
Terahertz (THz) sensing has been developed over the past three decades for concealed weapons detection, medical imaging, and non-destructive evaluation; however methods for THz image exploitation have not been well reported. We test a multiscale image fusion algorithm for the 2011 IEEE National Aerospace and Electronics Conf. (NAECON) Grand Challenge which consists of Terahertz (THz) and visual images. The study consists of image characterization (signals distribution), image processing (data fusion), and image analysis (edge detection). We found that THz image characterization did not necessarily follow a distinct Gaussian distribution, THz imagery fusion with visual data supported target detection, and that image analysis enhanced target assessment. For the initial experiment, we assess the target segmentation through edge detection, image fusion results, and image fusion quality assessment. The preliminary image exploitation and fusion results can further develop THz collection over clothing-obscured concealed weapons imaging, parameter optimization, and targeting evaluation.