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Vol. 157, Issue 10, October 2013, pp. 229-233

 

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Super-resolution Algorithm for Passive Millimeter Wave Imaging Based on Maximum Likelihood and Neighbor Wavelet Transform
 
Yiming Niu, Can Cui, Guo Yang, Wen Wu

Ministerial Key Laboratory of JGMT, Nanjing University of Science and Technology, Nanjing 210014, China
E-mail: nym1987@126.com

 

Received: 3 August 2013   /Accepted: 25 October 2013   /Published: 31 October 2013

Digital Sensors and Sensor Sysstems

 

Abstract: In passive millimeter wave imaging system, the problem of poor resolution of acquired image stems are mainly from system antenna size limitations. In order to improve the resolution of passive millimeter wave images, a super-resolution algorithm based on Maximum Likelihood estimation and neighbor wavelet transform are proposed in this paper. This algorithm first restores the spectrum in the pass-band and de-noises the image based on neighbor wavelet transform, then extrapolate the spectrum by using the non-linear projection operation Richardson-Lucy (RL) algorithm. Experimental results demonstrate the algorithm improve the convergent rate, enhance the resolution and reduces the ringing effects which are caused by regularizing the image restoration problem. Furthermore, the algorithm is easily implemented for passive millimeter wave imaging.

 

Keywords: Passive millimeter wave (PMMW) imaging, Radiometer, Super-resolution, Maximum likelihood.

 

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