Abstract

The design, development, and field-test results of a visible-band, folded, multiresolution, adaptive computational imaging system based on the Processing Arrays of Nyquist-limited Observations to Produce a Thin Electro-optic Sensor (PANOPTES) concept is presented. The architectural layout that enables this imager to be adaptive is described, and the control system that ensures reliable field-of-view steering for precision and accuracy in subpixel target registration is explained. A digital superresolution algorithm introduced to obtain high-resolution imagery from field tests conducted in both nighttime and daytime imaging conditions is discussed. The digital superresolution capability of this adaptive PANOPTES architecture is demonstrated via results in which resolution enhancement by a factor of 4 over the detector Nyquist limit is achieved.

© 2012 Optical Society of America

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    [CrossRef]
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2010 (1)

2009 (1)

2008 (2)

2007 (1)

2006 (3)

2003 (1)

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).
[CrossRef]

2001 (1)

1996 (1)

F. O. Huck, C. L. Fales, and Z. Rahman, “An information theory of visual communication,” Philos. Trans. R. Soc. A 354, 2193–2248 (1996).
[CrossRef]

1955 (1)

P. B. Fellgett and E. H. Linfoot, “On the assessment of optical images,” Philos. Trans. R. Soc. A 247, 369–407 (1955).
[CrossRef]

Athale, R.

R. Athale, D. M. Healy, D. J. Brady, and M. A. Neifeld, “Reinventing the camera,” Opt. Photon. News 19, 32–37 (2008).
[CrossRef]

Baldwin, K. B.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Barnard, R.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Behrmann, G.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Bhakta, V.

E. Faramarzi, V. Bhakta, D. Rajan, and M. Christensen, “Super resolution results in PANOPTES, an adaptive multi-aperture folded architecture,” in Proceedings of IEEE International Conference on Image Processing (ICIP 2010) (IEEE, 2010), pp. 2833–2836.

Bhakta, V. R.

V. R. Bhakta, M. Somayaji, S. C. Douglas, and M. P. Christensen, “Experimentally validated computational imaging with adaptive multiaperture folded architecture,” Appl. Opt. 49, B51–B58 (2010).
[CrossRef]

M. P. Christensen, V. R. Bhakta, D. Rajan, T. Mirani, S. C. Douglas, S. L. Wood, and M. W. Haney, “Adaptive flat multiresolution multiplexed computational imaging architecture utilizing micromirror arrays to steer subimager field of view,” Appl. Opt. 45, 2884–2892 (2006).
[CrossRef]

V. R. Bhakta and M. P. Christensen, “Performance metric for multi-aperture computational imaging sensor,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, Technical Digest (Optical Society of America, 2005), paper CMA5.

Blasche, G.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Brada, R.

D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 1988) (IEEE, 1988), pp. 742–746.

Brady, D.

Brady, D. J.

R. Athale, D. M. Healy, D. J. Brady, and M. A. Neifeld, “Reinventing the camera,” Opt. Photon. News 19, 32–37 (2008).
[CrossRef]

Carriere, J.

Chaparala, M. V.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Chen, C.

Christensen, M.

E. Faramarzi, V. Bhakta, D. Rajan, and M. Christensen, “Super resolution results in PANOPTES, an adaptive multi-aperture folded architecture,” in Proceedings of IEEE International Conference on Image Processing (ICIP 2010) (IEEE, 2010), pp. 2833–2836.

Christensen, M. P.

V. R. Bhakta, M. Somayaji, S. C. Douglas, and M. P. Christensen, “Experimentally validated computational imaging with adaptive multiaperture folded architecture,” Appl. Opt. 49, B51–B58 (2010).
[CrossRef]

M. P. Christensen, V. R. Bhakta, D. Rajan, T. Mirani, S. C. Douglas, S. L. Wood, and M. W. Haney, “Adaptive flat multiresolution multiplexed computational imaging architecture utilizing micromirror arrays to steer subimager field of view,” Appl. Opt. 45, 2884–2892 (2006).
[CrossRef]

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

I. Sinharoy, S. C. Douglas, D. Rajan, and M. P. Christensen, “Model-based region-of-interest estimation for adaptive resource allocation in multi-aperture imaging systems,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008) (IEEE, 2008), pp. 1961–1964.

V. R. Bhakta and M. P. Christensen, “Performance metric for multi-aperture computational imaging sensor,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, Technical Digest (Optical Society of America, 2005), paper CMA5.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Coyle, K.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Dillon, T.

Douglas, S.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Douglas, S. C.

Duparré, J. W.

J. W. Duparré, and F. C. Wippermann, “Micro-optical artificial compound eyes,” Bioinspiration Biomemetics 1, R1–R16(2006).
[CrossRef]

Fales, C. L.

F. O. Huck, C. L. Fales, and Z. Rahman, “An information theory of visual communication,” Philos. Trans. R. Soc. A 354, 2193–2248 (1996).
[CrossRef]

Faramarzi, E.

E. Faramarzi, V. Bhakta, D. Rajan, and M. Christensen, “Super resolution results in PANOPTES, an adaptive multi-aperture folded architecture,” in Proceedings of IEEE International Conference on Image Processing (ICIP 2010) (IEEE, 2010), pp. 2833–2836.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Fellgett, P. B.

P. B. Fellgett and E. H. Linfoot, “On the assessment of optical images,” Philos. Trans. R. Soc. A 247, 369–407 (1955).
[CrossRef]

Ford, J. E.

Frattin, D.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Gibbons, R.

Gill, J.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Granquist-Fraser, D.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Gray, B.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Haack, K.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Haney, M. W.

Hasenplaugh, W. C.

Healy, D. M.

R. Athale, D. M. Healy, D. J. Brady, and M. A. Neifeld, “Reinventing the camera,” Opt. Photon. News 19, 32–37 (2008).
[CrossRef]

Hopkins, R. E.

R. E. Hopkins, “Mirror and prism systems,” in Applied Optics and Optical Engineering, R. Kingslake, ed. (Academic, 1965), Vol. III, Chap. 7, pp. 269–308.

Huck, F. O.

F. O. Huck, C. L. Fales, and Z. Rahman, “An information theory of visual communication,” Philos. Trans. R. Soc. A 354, 2193–2248 (1996).
[CrossRef]

Kang, M. G.

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).
[CrossRef]

Keren, D.

D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 1988) (IEEE, 1988), pp. 742–746.

Kolste, R. T.

Krapels, K.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Kumagai, T.

Laine, J.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Linfoot, E. H.

P. B. Fellgett and E. H. Linfoot, “On the assessment of optical images,” Philos. Trans. R. Soc. A 247, 369–407 (1955).
[CrossRef]

Matthews, S.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Milojkovic, P.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Mirani, T.

Mirotznik, M.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Miyatake, S.

Morrison, R. L.

Myhr, S.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Neifeld, M. A.

R. Athale, D. M. Healy, D. J. Brady, and M. A. Neifeld, “Reinventing the camera,” Opt. Photon. News 19, 32–37 (2008).
[CrossRef]

P. M. Shankar, W. C. Hasenplaugh, R. L. Morrison, R. A. Stack, and M. A. Neifeld, “Multiaperture imaging,” Appl. Opt. 45, 2871–2883 (2006).
[CrossRef]

Ogunfemi, B.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Papamichalis, P.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Park, M. K.

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).
[CrossRef]

Park, S. C.

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).
[CrossRef]

Pauca, V. P.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Peleg, S.

D. Keren, S. Peleg, and R. Brada, “Image sequence enhancement using sub-pixel displacements,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 1988) (IEEE, 1988), pp. 742–746.

Pitsianis, N.

Plemmons, R. J.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Portnoy, A.

Prasad, S.

R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

Prather, D.

Rahman, Z.

F. O. Huck, C. L. Fales, and Z. Rahman, “An information theory of visual communication,” Philos. Trans. R. Soc. A 354, 2193–2248 (1996).
[CrossRef]

Rajan, D.

M. P. Christensen, V. R. Bhakta, D. Rajan, T. Mirani, S. C. Douglas, S. L. Wood, and M. W. Haney, “Adaptive flat multiresolution multiplexed computational imaging architecture utilizing micromirror arrays to steer subimager field of view,” Appl. Opt. 45, 2884–2892 (2006).
[CrossRef]

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

I. Sinharoy, S. C. Douglas, D. Rajan, and M. P. Christensen, “Model-based region-of-interest estimation for adaptive resource allocation in multi-aperture imaging systems,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008) (IEEE, 2008), pp. 1961–1964.

E. Faramarzi, V. Bhakta, D. Rajan, and M. Christensen, “Super resolution results in PANOPTES, an adaptive multi-aperture folded architecture,” in Proceedings of IEEE International Conference on Image Processing (ICIP 2010) (IEEE, 2010), pp. 2833–2836.

P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

Schulz, T.

Sebelius, P.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

Shankar, M.

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I. Sinharoy, S. C. Douglas, D. Rajan, and M. P. Christensen, “Model-based region-of-interest estimation for adaptive resource allocation in multi-aperture imaging systems,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008) (IEEE, 2008), pp. 1961–1964.

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M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

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R. J. Plemmons, S. Prasad, S. Matthews, M. Mirotznik, R. Barnard, B. Gray, V. P. Pauca, T. C. Torgersen, J. van der Gracht, and G. Behrmann, “PERIODIC: integrated computational array imaging technology,” in Adaptive Optics: Analysis and Methods/Computational Optical Sensing and Imaging/Information Photonics/Signal Recovery and Synthesis Topical Meetings on CD-ROM, OSA Technical Digest (CD) (Optical Society of America, 2007), paper CMA1.

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P. Milojkovic, J. Gill, D. Frattin, K. Coyle, K. Haack, S. Myhr, D. Rajan, S. Douglas, P. Papamichalis, M. Somayaji, M. P. Christensen, and K. Krapels, “Multichannel, agile, computationally enhanced camera based on PANOPTES architecture,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2009), paper CTuB4.

M. Somayaji, M. P. Christensen, E. Faramarzi, D. Rajan, J. Laine, D. Granquist-Fraser, P. Sebelius, A. Zachai, M. V. Chaparala, G. Blasche, K. B. Baldwin, and B. Ogunfemi, “Field test of PANOPTES-based adaptive computational imaging system prototype,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CPDP3.

I. Sinharoy, S. C. Douglas, D. Rajan, and M. P. Christensen, “Model-based region-of-interest estimation for adaptive resource allocation in multi-aperture imaging systems,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008) (IEEE, 2008), pp. 1961–1964.

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Figures (9)

Fig. 1.
Fig. 1.

(a) Aerial image of an airport terminal and (b) information content map identifying regions of interest within the original image shown in (a).

Fig. 2.
Fig. 2.

Conceptual design layout of the PANOPTES prototype.

Fig. 3.
Fig. 3.

Frontal photograph of the PANOPTES prototype, as built and tested. The WFOV imager lens (surrounded by internal baffles) is visible in the center. The NFOV entrance apertures are open and visible in the outer limbs of the pan-tilt arms.

Fig. 4.
Fig. 4.

Boresight calibration using a collimated beam. The variables fW and fN are the WFOV and NFOV imagers’ focal lengths, respectively, while A1 is the distance from the NFOV lens to the center of M1, and A2 is the distance from the center of M1 to that of M2. The NFOV optical axis intersects the centers of M1, M2 and the NFOV lens.

Fig. 5.
Fig. 5.

DSR forward model.

Fig. 6.
Fig. 6.

Nighttime testing targets. (a) Calibration and resolution targets, which were a back-illuminated trailer with four different sized bar patterns, resolution posters and a calibration plate on a tripod on the left-hand side of the image, and (b) the target Humvee.

Fig. 7.
Fig. 7.

Results of SRUM algorithm applied to nighttime images of bar targets. The left column shows one of the original LR images and the right column presents the reconstructed HR images. The target ranges were 300, 800, and 1800 m for the top, middle, and bottom rows, respectively. The inset text represents spatial frequencies of the targets as multiples of detector Nyquist, with green indicating that the target was resolved and yellow meaning it was unresolved.

Fig. 8.
Fig. 8.

Results of the SRUM algorithm applied to nighttime images of the Humvee. The left column shows one of the original LR mages and the right column presents the reconstructed HR images. The target ranges were 300 and 800 m for the top and bottom rows, respectively.

Fig. 9.
Fig. 9.

Results of the SRUM algorithm applied to some daytime images. The left column shows one of the original LR images and the right column presents the reconstructed HR images. The target ranges were 800 and <50m for the top and bottom rows, respectively.

Equations (16)

Equations on this page are rendered with MathJax. Learn more.

θM1=sec1(R3(R2+Y2A22)1/2(A22R2)2+2A23R2YA2R4YA24R(R2+Y2A22)1/2(A22R2)3+A25Y(R2Y2)(A22R2)3(R2+Y2)),
θM2=tan1(A1Z(R2+Y2A22)1/2),
gk(x,y)=(fwk(x,y)hk(x,y))L+nk(x,y),k=1,,N,
[xy]=zk[cos(θk)sin(θk)sin(θk)cos(θk)][xy]+[sxksyk].
gk=Wkf+nk,k=1,,P,
Wk=DkHkSk,
g=Wf+n,
fn+1=fnλnn=fnλn[WT(HWfng)+γLTLfn],
H=I+βHhp,
λn=¯nT(HWfng)+γ¯¯nTLfn¯nTW¯n+γ¯¯nT¯¯n,
λn=n2WnH2+γLn2,
J(fn)=fnTWTHWfn2fnTWTg+γfnTLTLfn.
fn+1=fnλnn.
λn=argminJ(fn+1)λn=argminJ(fnλnn)λn
J(fnλnn)λn=0λn{(fnλnn)TWTHW(fnλnn)2(fnλnn)TWTg+γ(fnλnn)TLTL(fnλnn)}=0.
2nTWTHWfn+2λnnTWTHWn2nTWTg2γnTLTLfn+2γλnnTLTLn=2nT[WT(HWfng)]n+2λn[(Wn)TH(Wn)+γ(Lfn)T(Lfn)]=2n2+2λn[WnH2+γLn2]=0,

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