A single-frame terahertz image super-resolution reconstruction method based on sparse representation theory

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.