Journal of the European Optical Society - Rapid publications, Vol 9 (2014)
Quantitative characterization of super-resolution infrared imaging based on time-varying focal plane coding
Abstract
High resolution infrared image has been the goal of an infrared imaging system. In this paper, a super-resolution infrared imaging method using time-varying coded mask is proposed based on focal plane coding and compressed sensing theory. The basic idea of this method is to set a coded mask on the focal plane of the optical system, and the same scene could be sampled many times repeatedly by using time-varying control coding strategy, the super-resolution image is further reconstructed by sparse optimization algorithm. The results of simulation are quantitatively evaluated by introducing the Peak Signal-to-Noise Ratio (PSNR) and Modulation Transfer Function (MTF), which illustrate that the effect of compressed measurement coefficient r and coded mask resolution m on the reconstructed image quality. Research results show that the proposed method will promote infrared imaging quality effectively, which will be helpful for the practical design of new type of high resolution infrared imaging systems.
© The Authors. All rights reserved. [DOI: 10.2971/jeos.2014.14043]
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Cite this articleReferences
F. Jinxiang, and Y. Yanjun, ”Development in new concepts and new schemes for military infrared imaging systems,” Infrared Laser Eng. 40, 1–6 (2011).
F. Jinxiang, and Y. Yanjun, ”Development trends of infrared detecting technology,” Infrared Laser Eng. 41, 3145–3153 (2012).
D. L. Donoho, ”Compressed sensing,” IEEE T. Inform. Theory 52, 1289–1306 (2006).
Y. Tsaig, and D. L. Donoho, ”Extensions of compressed sensing,” Signal Process 86, 549–571 (2006).
A. D. Portnoy, N. P. Pitsianis, D. J. Brady, J. Guo, M. A. Fiddy, M. R. Feldman, and R. D. Te Kolste, ”Thin digital imaging systems using focal plane coding,” Proc. SPIE 6065, 60650F (2006).
A. D. Portnoy, N. P. Pitsianis, X. Sun, and D. J. Brady, ”Multichannel sampling schemes for optical imaging systems,” Appl. Optics 47, B76–B85 (2008).
N. Pitsianis, D. Brady, A. Portnoy, X. Sun, T. Suleski, M. Fiddy, M. Feldman, and R. TeKolste, ”Compressive imaging sensors,” Proc. SPIE 6232, 62320A (2006).
R. G. Baraniuk, ”Single-pixel imaging via compressive sampling,” IEEE Signal Proc. Mag. 25, 83–91 (2008).
N. Gopalsami, S. Liao, T. W. Elmer, E. R. Koehl, A. Heifetz, A. C. Raptis, L. Spinoulas, and A. K. Katsaggelos, ”Passive millimeter-wave imaging with compressive sensing,” Opt. Eng. 51, 091614–1 (2012).
L. Xiao, K. Liu, D. Han, and J. Liu, ”Focal plane coding method for high resolution infrared imaging,” Infrared Laser Eng. 40, 2065–2070 (2011).
L.-L. Xiao, K. Liu, D.-P. Han, and J.-Y. Liu, ”A compressed sensing approach for enhancing infrared imaging resolution,” Opt. Laser Technol. 44, 2354–2360 (2012).
E. J. Candes, ”The restricted isometry property and its implications for compressed sensing,” C. R. Math. 346, 589–592 (2008).
J. Haupt, and R. Nowak, ”Signal reconstruction from noisy random projections,” IEEE T. Inform. Theory 52, 4036–4048 (2006).
E. J. Candes, and T. Tao, ”Decoding by linear programming,” IEEE T. Inform. Theory 51, 4203–4215 (2005).
E. J. Candes, J. K. Romberg, and T. Tao, ”Stable signal recovery from incomplete and inaccurate measurements,” Commun Pur. Appl. Math. 59, 1207–1223 (2006).
G.-M. Shi, D.-H. Liu, D. Gao, Z. Liu, J. Lin, and L.-J. Wang, ”Advances in theory and application of compressed sensing,” Acta Electron. 37, 1070–1081 (2009).
W. U. Bajwa, J. D. Haupt, G. M. Raz, S. J. Wright, and R. D. Nowak, ”Toeplitz-structured compressed sensing matrices,” in Proceedings of Statistical Signal Processing, 2007. SSP’07. IEEE/SP 14th Workshop on, 294–298 (IEEE, Madison, 2007).
M. A. Figueiredo, R. D. Nowak, and S. J. Wright, ”Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems,” IEEE J. Sel. Top. Signa. 1, 586–597 (2007).
C. Bo-liang, ”Development state of IRFPA imaging device [J],” Infrared Laser Eng. 1, 000 (2005).
X.-P. Shao, C. Zhong, J. Du, and C.-C. Rao, ”Super-resolution imaging method using multi-value compressed coded aperture,” J. Optoelectronics Laser 6, 032 (2012).
Y. Li, and B. He, ”Quantitative evaluation of image quality of CCD subpixel imaging using MTF,” Infrared Laser Eng. 42, (2013).
F. B. Xu Baoshu, and S. Zelin, ”Modulation Transfer Function Measurement Method of Electro-optical Imaging System,” Acta Optica Sin. 31, 1111004 (2011).