Recent Progress in Computational Imaging Through Turbid Media 


Vol. 39,  No. 12, pp. 764-770, Dec.  2014


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  Abstract

It is expected that the techniques of optical imaging through turbid media enables non-invasive imaging through human skin and biological tissues. In recent years, many researches have shown that imaging through turbid media can be made possible by measuring the transmission matrix (TM) of the turbid medium and utilizing it for image recovery. However, this TM based image recovery requires a huge amount of data acquisition and post signal processing of them. Very recently, there were new results that this problem of huge data acquisition and processing can be resolved by using the compressed sensing (CS) framework. CS is a relatively new signal acquisition and reconstruction framework which makes possible to recover the signal of interest correctly with significantly smaller number of signal measurements. In this paper, the TM-based image recovery in imaging through turbid media is reviewed and the recent progress made by using CS is introduced.

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  Cite this article

[IEEE Style]

H. Jang, C. Yoon, E. Chung, W. Choi, H. Lee, "Recent Progress in Computational Imaging Through Turbid Media," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 12, pp. 764-770, 2014. DOI: .

[ACM Style]

Hwanchol Jang, Changhyeong Yoon, Euiheon Chung, Wonshik Choi, and Heung-No Lee. 2014. Recent Progress in Computational Imaging Through Turbid Media. The Journal of Korean Institute of Communications and Information Sciences, 39, 12, (2014), 764-770. DOI: .

[KICS Style]

Hwanchol Jang, Changhyeong Yoon, Euiheon Chung, Wonshik Choi, Heung-No Lee, "Recent Progress in Computational Imaging Through Turbid Media," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 12, pp. 764-770, 12. 2014.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880