Paper
11 November 2014 A single-frame terahertz image super-resolution reconstruction method based on sparse representation theory
Yue Li, Yuan-meng Zhao, Chao Deng, Cunlin Zhang
Author Affiliations +
Abstract
Terrorist attacks make the public safety issue becoming the focus of national attention. Passive terahertz security instrument can help overcomesome shortcomings with current security instruments. Terahertz wave has a strong penetrating power which can pass through clothes without harming human bodies and detected objects. However, in the lab experiments, we found that original terahertz imagesobtained by passive terahertz technique were often too vague to detect the objects of interest. Prior studies suggest that learning-based image super-resolution reconstruction(SRR) method can solve this problem. To our knowledge, we applied the learning-based image SRR method for the first time in single-frame passive terahertz image processing. Experimental results showed that the processed passive terahertz images wereclearer and easier to identify suspicious objects than the original images. We also compare our method with three conventional methods and our method show greater advantage over the other methods.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yue Li, Yuan-meng Zhao, Chao Deng, and Cunlin Zhang "A single-frame terahertz image super-resolution reconstruction method based on sparse representation theory", Proc. SPIE 9275, Infrared, Millimeter-Wave, and Terahertz Technologies III, 92751N (11 November 2014); https://doi.org/10.1117/12.2073964
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KEYWORDS
Associative arrays

Terahertz radiation

Lawrencium

Chemical species

Image resolution

Super resolution

Image compression

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