Abstract

For the Time Delay Integration (TDI) staggered line-scanning thermal infrared imager, a Computational Imaging (CI) approach is developed to achieve higher spatial resolution images. After a thorough analysis of the causes of non-uniform image displacement and degradation for multi-channel staggered TDI arrays, the study aims to approach one-dimensional (1D) sub-pixel displacement estimation and superposition of images from time-division multiplexing scanning lines. Under the assumption that a thermal image is 2D piecewise C2 smooth, a sparse-and-smooth deconvolution algorithm with L1-norm regularization terms combining the first and second order derivative operators is proposed to restore high frequency components and to suppress aliasing simultaneously. It is theoretically and experimentally demonstrated, with simulation and airborne thermal infrared images, that this is a state-of-the-art practical CI method to reconstruct clear images with higher frequency components from raw thermal images that are subject to instantaneous distortion and blurring.

© 2015 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Restoration of images captured by a staggered time delay and integration camera in the presence of mechanical vibrations

Gadi Hochman, Yitzhak Yitzhaky, Norman S. Kopeika, Yair Lauber, Meira Citroen, and Adrian Stern
Appl. Opt. 43(22) 4345-4354 (2004)

Registration of motion-distorted interlaced images captured by a scanning vector imaging sensor

A. Avrin, A. Stern, and N. S. Kopeika
Appl. Opt. 45(23) 5950-5959 (2006)

Simple and efficient approach for restoration of non-uniformly warped images

Kalyan Kumar Halder, Murat Tahtali, and Sreenatha G. Anavatti
Appl. Opt. 53(25) 5576-5584 (2014)

References

  • View by:
  • |
  • |
  • |

  1. G. Hochman, Y. Yitzhaky, N. S. Kopeika, Y. Lauber, M. Citroen, and A. Stern, “Restoration of images captured by a staggered time delay and integration camera in the presence of mechanical vibrations,” Appl. Opt. 43(22), 4345–4354 (2004).
    [Crossref] [PubMed]
  2. A. Averbuch, G. Liron, and B. Z. Bobrovsky, “Scene based Non-Uniformity Correction in Thermal images using Kalman Filter,” Image Vis. Comput. 25(6), 833–851 (2007).
    [Crossref]
  3. J. Mait, R. Athale, and J. van der Gracht, “Evolutionary paths in imaging and recent trends,” Opt. Express 11(18), 2093–2101 (2003).
    [Crossref] [PubMed]
  4. J. Tanida, T. Kumagai, K. Yamada, S. Miyatake, K. Ishida, T. Morimoto, N. Kondou, D. Miyazaki, and Y. Ichioka, “Thin observation module by bound optics (TOMBO): concept and experimental verification,” Appl. Opt. 40(11), 1806–1813 (2001).
    [Crossref] [PubMed]
  5. M. Shankar, R. Willett, N. Pitsianis, T. Schulz, R. Gibbons, R. Te Kolste, J. Carriere, C. Chen, D. Prather, and D. Brady, “Thin infrared imaging systems through multichannel sampling,” Appl. Opt. 47(10), B1–B10 (2008).
    [Crossref] [PubMed]
  6. A. Stern and B. Javidi, “Three-dimensional image sensing and reconstruction with time-division multiplexed computational integral imaging,” Appl. Opt. 42(35), 7036–7042 (2003).
    [Crossref] [PubMed]
  7. R. Horisaki, T. Nakamura, and J. Tanida, “Superposition Imaging for Three-Dimensionally Space-Invariant Point Spread Functions,” Appl. Phys. Express 4(11), 112501 (2011).
    [Crossref]
  8. J. S. Jang and B. Javidi, “Improved viewing resolution of three-dimensional integral imaging by use of nonstationary micro-optics,” Opt. Lett. 27(5), 324–326 (2002).
    [Crossref] [PubMed]
  9. L. J. Kozlowski and W. F. Kosonocky, “Infrared detector arrays” in Handbook of Optics, 3rd edition, M. Bass, editor (McGraw-Hill, 2009), Volume II, Chapter 33.
  10. H. S. Wong, Y. L. Yao, and E. S. Schlig, “TDI charge coupled-devices: Design and applications,” IBM J. Res. Develop. 36(1), 83–106 (1992).
    [Crossref]
  11. D. Wang, T. Zhang, and H. Kuang, “Clocking smear analysis and reduction for multi phase TDI CCD in remote sensing system,” Opt. Express 19(6), 4868–4880 (2011).
    [Crossref] [PubMed]
  12. S. L. Smith, J. Mooney, T. A. Tantalo, and R. D. Fiete, “Understanding image quality losses due to smear in high resolution remote sensing imaging system,” Opt. Eng. 38(5), 821–826 (1999).
    [Crossref]
  13. O. Hadar, M. Fisher, and N. S. Kopeika, “Image resolution limits resulting from mechanical vibration. Part III: numerical calculation of modulation transfer function,” Opt. Eng. 31(3), 581–589 (1992).
    [Crossref]
  14. S. Raiter, A. Stern, O. Hadar, and N. S. Kopeika, “Image restoration from camera vibration and object motion blur in infrared staggered time-delay and integration systems,” Opt. Eng. 42(11), 3253–3264 (2003).
    [Crossref]
  15. H. Yan and J. G. Liu, “Robust sub-pixel disparity estimation and its refinement around depth discontinuity and featureless areas,” inProceedings of IEEE International Geoscience and Remote Sensing Symposium (IEEE, 2010),pp 4576–4579.
    [Crossref]
  16. A. Stern and N. S. Kopeika, “Motion-distorted composite-frame restoration,” Appl. Opt. 38(5), 757–765 (1999).
    [Crossref] [PubMed]
  17. A. Avrin, A. Stern, and N. S. Kopeika, “Registration of motion-distorted interlaced images captured by a scanning vector imaging sensor,” Appl. Opt. 45(23), 5950–5959 (2006).
    [Crossref] [PubMed]
  18. E. Baltsavias, S. Kocaman, D. Akca, and K. Wolff, “Geometric and radiometric investigations of cartosat-1 data,” presented at ISPRS Workshop “High Resolution Earth Imaging for Geospatial Information”, Hannover, Germany, May 29-June 1 2007.
  19. M. S. Scholl, “Thermal considerations in the design of a dynamic IR target,” Appl. Opt. 21(4), 660–667 (1982).
    [Crossref] [PubMed]
  20. W. Stefan, R. A. Renaut, and A. Gelb, “Improved total variation-type regularization using higher-order edge detectors,” SIAM J. Imaging Sci. 3(2), 232–251 (2010).
    [Crossref]
  21. M. Lysaker and X. C. Tai, “Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional,” Int. J. Comput. Vis. 66(1), 5–18 (2006).
    [Crossref]
  22. T. Sun, J. Liu, H. Yan, G. Morgan, and W. Chen, “Super-resolution reconstruction based on incoherent optical aperture synthesis,” Opt. Lett. 38(17), 3471–3474 (2013).
    [Crossref] [PubMed]
  23. Y. Yitzhaky and A. Stern, “Restoration of interlaced images degraded by variable velocity motion,” Opt. Eng. 42(12), 3557–3565 (2003).
    [Crossref]
  24. M. Fuhry and L. Reichel, “A new Tikhonov regularization method,” Numer. Algorithms 59(3), 433–445 (2012).
    [Crossref]
  25. M. Lysaker, A. Lundervold, and X. C. Tai, “Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time,” IEEE Trans. Image Process. 12(12), 1579–1590 (2003).
    [Crossref] [PubMed]
  26. G. Chiandussi, G. Bugeda, and E. Onate, “Shape variable definition with C0, C1 and C2 continuity functions,” Comput. Methods Appl. Mech. Eng. 188(4), 727–742 (2000).
    [Crossref]

2013 (1)

2012 (1)

M. Fuhry and L. Reichel, “A new Tikhonov regularization method,” Numer. Algorithms 59(3), 433–445 (2012).
[Crossref]

2011 (2)

R. Horisaki, T. Nakamura, and J. Tanida, “Superposition Imaging for Three-Dimensionally Space-Invariant Point Spread Functions,” Appl. Phys. Express 4(11), 112501 (2011).
[Crossref]

D. Wang, T. Zhang, and H. Kuang, “Clocking smear analysis and reduction for multi phase TDI CCD in remote sensing system,” Opt. Express 19(6), 4868–4880 (2011).
[Crossref] [PubMed]

2010 (1)

W. Stefan, R. A. Renaut, and A. Gelb, “Improved total variation-type regularization using higher-order edge detectors,” SIAM J. Imaging Sci. 3(2), 232–251 (2010).
[Crossref]

2008 (1)

2007 (1)

A. Averbuch, G. Liron, and B. Z. Bobrovsky, “Scene based Non-Uniformity Correction in Thermal images using Kalman Filter,” Image Vis. Comput. 25(6), 833–851 (2007).
[Crossref]

2006 (2)

M. Lysaker and X. C. Tai, “Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional,” Int. J. Comput. Vis. 66(1), 5–18 (2006).
[Crossref]

A. Avrin, A. Stern, and N. S. Kopeika, “Registration of motion-distorted interlaced images captured by a scanning vector imaging sensor,” Appl. Opt. 45(23), 5950–5959 (2006).
[Crossref] [PubMed]

2004 (1)

2003 (5)

M. Lysaker, A. Lundervold, and X. C. Tai, “Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time,” IEEE Trans. Image Process. 12(12), 1579–1590 (2003).
[Crossref] [PubMed]

S. Raiter, A. Stern, O. Hadar, and N. S. Kopeika, “Image restoration from camera vibration and object motion blur in infrared staggered time-delay and integration systems,” Opt. Eng. 42(11), 3253–3264 (2003).
[Crossref]

Y. Yitzhaky and A. Stern, “Restoration of interlaced images degraded by variable velocity motion,” Opt. Eng. 42(12), 3557–3565 (2003).
[Crossref]

J. Mait, R. Athale, and J. van der Gracht, “Evolutionary paths in imaging and recent trends,” Opt. Express 11(18), 2093–2101 (2003).
[Crossref] [PubMed]

A. Stern and B. Javidi, “Three-dimensional image sensing and reconstruction with time-division multiplexed computational integral imaging,” Appl. Opt. 42(35), 7036–7042 (2003).
[Crossref] [PubMed]

2002 (1)

2001 (1)

2000 (1)

G. Chiandussi, G. Bugeda, and E. Onate, “Shape variable definition with C0, C1 and C2 continuity functions,” Comput. Methods Appl. Mech. Eng. 188(4), 727–742 (2000).
[Crossref]

1999 (2)

S. L. Smith, J. Mooney, T. A. Tantalo, and R. D. Fiete, “Understanding image quality losses due to smear in high resolution remote sensing imaging system,” Opt. Eng. 38(5), 821–826 (1999).
[Crossref]

A. Stern and N. S. Kopeika, “Motion-distorted composite-frame restoration,” Appl. Opt. 38(5), 757–765 (1999).
[Crossref] [PubMed]

1992 (2)

O. Hadar, M. Fisher, and N. S. Kopeika, “Image resolution limits resulting from mechanical vibration. Part III: numerical calculation of modulation transfer function,” Opt. Eng. 31(3), 581–589 (1992).
[Crossref]

H. S. Wong, Y. L. Yao, and E. S. Schlig, “TDI charge coupled-devices: Design and applications,” IBM J. Res. Develop. 36(1), 83–106 (1992).
[Crossref]

1982 (1)

Athale, R.

Averbuch, A.

A. Averbuch, G. Liron, and B. Z. Bobrovsky, “Scene based Non-Uniformity Correction in Thermal images using Kalman Filter,” Image Vis. Comput. 25(6), 833–851 (2007).
[Crossref]

Avrin, A.

Bobrovsky, B. Z.

A. Averbuch, G. Liron, and B. Z. Bobrovsky, “Scene based Non-Uniformity Correction in Thermal images using Kalman Filter,” Image Vis. Comput. 25(6), 833–851 (2007).
[Crossref]

Brady, D.

Bugeda, G.

G. Chiandussi, G. Bugeda, and E. Onate, “Shape variable definition with C0, C1 and C2 continuity functions,” Comput. Methods Appl. Mech. Eng. 188(4), 727–742 (2000).
[Crossref]

Carriere, J.

Chen, C.

Chen, W.

Chiandussi, G.

G. Chiandussi, G. Bugeda, and E. Onate, “Shape variable definition with C0, C1 and C2 continuity functions,” Comput. Methods Appl. Mech. Eng. 188(4), 727–742 (2000).
[Crossref]

Citroen, M.

Fiete, R. D.

S. L. Smith, J. Mooney, T. A. Tantalo, and R. D. Fiete, “Understanding image quality losses due to smear in high resolution remote sensing imaging system,” Opt. Eng. 38(5), 821–826 (1999).
[Crossref]

Fisher, M.

O. Hadar, M. Fisher, and N. S. Kopeika, “Image resolution limits resulting from mechanical vibration. Part III: numerical calculation of modulation transfer function,” Opt. Eng. 31(3), 581–589 (1992).
[Crossref]

Fuhry, M.

M. Fuhry and L. Reichel, “A new Tikhonov regularization method,” Numer. Algorithms 59(3), 433–445 (2012).
[Crossref]

Gelb, A.

W. Stefan, R. A. Renaut, and A. Gelb, “Improved total variation-type regularization using higher-order edge detectors,” SIAM J. Imaging Sci. 3(2), 232–251 (2010).
[Crossref]

Gibbons, R.

Hadar, O.

S. Raiter, A. Stern, O. Hadar, and N. S. Kopeika, “Image restoration from camera vibration and object motion blur in infrared staggered time-delay and integration systems,” Opt. Eng. 42(11), 3253–3264 (2003).
[Crossref]

O. Hadar, M. Fisher, and N. S. Kopeika, “Image resolution limits resulting from mechanical vibration. Part III: numerical calculation of modulation transfer function,” Opt. Eng. 31(3), 581–589 (1992).
[Crossref]

Hochman, G.

Horisaki, R.

R. Horisaki, T. Nakamura, and J. Tanida, “Superposition Imaging for Three-Dimensionally Space-Invariant Point Spread Functions,” Appl. Phys. Express 4(11), 112501 (2011).
[Crossref]

Ichioka, Y.

Ishida, K.

Jang, J. S.

Javidi, B.

Kondou, N.

Kopeika, N. S.

A. Avrin, A. Stern, and N. S. Kopeika, “Registration of motion-distorted interlaced images captured by a scanning vector imaging sensor,” Appl. Opt. 45(23), 5950–5959 (2006).
[Crossref] [PubMed]

G. Hochman, Y. Yitzhaky, N. S. Kopeika, Y. Lauber, M. Citroen, and A. Stern, “Restoration of images captured by a staggered time delay and integration camera in the presence of mechanical vibrations,” Appl. Opt. 43(22), 4345–4354 (2004).
[Crossref] [PubMed]

S. Raiter, A. Stern, O. Hadar, and N. S. Kopeika, “Image restoration from camera vibration and object motion blur in infrared staggered time-delay and integration systems,” Opt. Eng. 42(11), 3253–3264 (2003).
[Crossref]

A. Stern and N. S. Kopeika, “Motion-distorted composite-frame restoration,” Appl. Opt. 38(5), 757–765 (1999).
[Crossref] [PubMed]

O. Hadar, M. Fisher, and N. S. Kopeika, “Image resolution limits resulting from mechanical vibration. Part III: numerical calculation of modulation transfer function,” Opt. Eng. 31(3), 581–589 (1992).
[Crossref]

Kuang, H.

Kumagai, T.

Lauber, Y.

Liron, G.

A. Averbuch, G. Liron, and B. Z. Bobrovsky, “Scene based Non-Uniformity Correction in Thermal images using Kalman Filter,” Image Vis. Comput. 25(6), 833–851 (2007).
[Crossref]

Liu, J.

Liu, J. G.

H. Yan and J. G. Liu, “Robust sub-pixel disparity estimation and its refinement around depth discontinuity and featureless areas,” inProceedings of IEEE International Geoscience and Remote Sensing Symposium (IEEE, 2010),pp 4576–4579.
[Crossref]

Lundervold, A.

M. Lysaker, A. Lundervold, and X. C. Tai, “Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time,” IEEE Trans. Image Process. 12(12), 1579–1590 (2003).
[Crossref] [PubMed]

Lysaker, M.

M. Lysaker and X. C. Tai, “Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional,” Int. J. Comput. Vis. 66(1), 5–18 (2006).
[Crossref]

M. Lysaker, A. Lundervold, and X. C. Tai, “Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time,” IEEE Trans. Image Process. 12(12), 1579–1590 (2003).
[Crossref] [PubMed]

Mait, J.

Miyatake, S.

Miyazaki, D.

Mooney, J.

S. L. Smith, J. Mooney, T. A. Tantalo, and R. D. Fiete, “Understanding image quality losses due to smear in high resolution remote sensing imaging system,” Opt. Eng. 38(5), 821–826 (1999).
[Crossref]

Morgan, G.

Morimoto, T.

Nakamura, T.

R. Horisaki, T. Nakamura, and J. Tanida, “Superposition Imaging for Three-Dimensionally Space-Invariant Point Spread Functions,” Appl. Phys. Express 4(11), 112501 (2011).
[Crossref]

Onate, E.

G. Chiandussi, G. Bugeda, and E. Onate, “Shape variable definition with C0, C1 and C2 continuity functions,” Comput. Methods Appl. Mech. Eng. 188(4), 727–742 (2000).
[Crossref]

Pitsianis, N.

Prather, D.

Raiter, S.

S. Raiter, A. Stern, O. Hadar, and N. S. Kopeika, “Image restoration from camera vibration and object motion blur in infrared staggered time-delay and integration systems,” Opt. Eng. 42(11), 3253–3264 (2003).
[Crossref]

Reichel, L.

M. Fuhry and L. Reichel, “A new Tikhonov regularization method,” Numer. Algorithms 59(3), 433–445 (2012).
[Crossref]

Renaut, R. A.

W. Stefan, R. A. Renaut, and A. Gelb, “Improved total variation-type regularization using higher-order edge detectors,” SIAM J. Imaging Sci. 3(2), 232–251 (2010).
[Crossref]

Schlig, E. S.

H. S. Wong, Y. L. Yao, and E. S. Schlig, “TDI charge coupled-devices: Design and applications,” IBM J. Res. Develop. 36(1), 83–106 (1992).
[Crossref]

Scholl, M. S.

Schulz, T.

Shankar, M.

Smith, S. L.

S. L. Smith, J. Mooney, T. A. Tantalo, and R. D. Fiete, “Understanding image quality losses due to smear in high resolution remote sensing imaging system,” Opt. Eng. 38(5), 821–826 (1999).
[Crossref]

Stefan, W.

W. Stefan, R. A. Renaut, and A. Gelb, “Improved total variation-type regularization using higher-order edge detectors,” SIAM J. Imaging Sci. 3(2), 232–251 (2010).
[Crossref]

Stern, A.

Sun, T.

Tai, X. C.

M. Lysaker and X. C. Tai, “Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional,” Int. J. Comput. Vis. 66(1), 5–18 (2006).
[Crossref]

M. Lysaker, A. Lundervold, and X. C. Tai, “Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time,” IEEE Trans. Image Process. 12(12), 1579–1590 (2003).
[Crossref] [PubMed]

Tanida, J.

Tantalo, T. A.

S. L. Smith, J. Mooney, T. A. Tantalo, and R. D. Fiete, “Understanding image quality losses due to smear in high resolution remote sensing imaging system,” Opt. Eng. 38(5), 821–826 (1999).
[Crossref]

Te Kolste, R.

van der Gracht, J.

Wang, D.

Willett, R.

Wong, H. S.

H. S. Wong, Y. L. Yao, and E. S. Schlig, “TDI charge coupled-devices: Design and applications,” IBM J. Res. Develop. 36(1), 83–106 (1992).
[Crossref]

Yamada, K.

Yan, H.

T. Sun, J. Liu, H. Yan, G. Morgan, and W. Chen, “Super-resolution reconstruction based on incoherent optical aperture synthesis,” Opt. Lett. 38(17), 3471–3474 (2013).
[Crossref] [PubMed]

H. Yan and J. G. Liu, “Robust sub-pixel disparity estimation and its refinement around depth discontinuity and featureless areas,” inProceedings of IEEE International Geoscience and Remote Sensing Symposium (IEEE, 2010),pp 4576–4579.
[Crossref]

Yao, Y. L.

H. S. Wong, Y. L. Yao, and E. S. Schlig, “TDI charge coupled-devices: Design and applications,” IBM J. Res. Develop. 36(1), 83–106 (1992).
[Crossref]

Yitzhaky, Y.

Zhang, T.

Appl. Opt. (7)

Appl. Phys. Express (1)

R. Horisaki, T. Nakamura, and J. Tanida, “Superposition Imaging for Three-Dimensionally Space-Invariant Point Spread Functions,” Appl. Phys. Express 4(11), 112501 (2011).
[Crossref]

Comput. Methods Appl. Mech. Eng. (1)

G. Chiandussi, G. Bugeda, and E. Onate, “Shape variable definition with C0, C1 and C2 continuity functions,” Comput. Methods Appl. Mech. Eng. 188(4), 727–742 (2000).
[Crossref]

IBM J. Res. Develop. (1)

H. S. Wong, Y. L. Yao, and E. S. Schlig, “TDI charge coupled-devices: Design and applications,” IBM J. Res. Develop. 36(1), 83–106 (1992).
[Crossref]

IEEE Trans. Image Process. (1)

M. Lysaker, A. Lundervold, and X. C. Tai, “Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time,” IEEE Trans. Image Process. 12(12), 1579–1590 (2003).
[Crossref] [PubMed]

Image Vis. Comput. (1)

A. Averbuch, G. Liron, and B. Z. Bobrovsky, “Scene based Non-Uniformity Correction in Thermal images using Kalman Filter,” Image Vis. Comput. 25(6), 833–851 (2007).
[Crossref]

Int. J. Comput. Vis. (1)

M. Lysaker and X. C. Tai, “Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional,” Int. J. Comput. Vis. 66(1), 5–18 (2006).
[Crossref]

Numer. Algorithms (1)

M. Fuhry and L. Reichel, “A new Tikhonov regularization method,” Numer. Algorithms 59(3), 433–445 (2012).
[Crossref]

Opt. Eng. (4)

Y. Yitzhaky and A. Stern, “Restoration of interlaced images degraded by variable velocity motion,” Opt. Eng. 42(12), 3557–3565 (2003).
[Crossref]

S. L. Smith, J. Mooney, T. A. Tantalo, and R. D. Fiete, “Understanding image quality losses due to smear in high resolution remote sensing imaging system,” Opt. Eng. 38(5), 821–826 (1999).
[Crossref]

O. Hadar, M. Fisher, and N. S. Kopeika, “Image resolution limits resulting from mechanical vibration. Part III: numerical calculation of modulation transfer function,” Opt. Eng. 31(3), 581–589 (1992).
[Crossref]

S. Raiter, A. Stern, O. Hadar, and N. S. Kopeika, “Image restoration from camera vibration and object motion blur in infrared staggered time-delay and integration systems,” Opt. Eng. 42(11), 3253–3264 (2003).
[Crossref]

Opt. Express (2)

Opt. Lett. (2)

SIAM J. Imaging Sci. (1)

W. Stefan, R. A. Renaut, and A. Gelb, “Improved total variation-type regularization using higher-order edge detectors,” SIAM J. Imaging Sci. 3(2), 232–251 (2010).
[Crossref]

Other (3)

E. Baltsavias, S. Kocaman, D. Akca, and K. Wolff, “Geometric and radiometric investigations of cartosat-1 data,” presented at ISPRS Workshop “High Resolution Earth Imaging for Geospatial Information”, Hannover, Germany, May 29-June 1 2007.

H. Yan and J. G. Liu, “Robust sub-pixel disparity estimation and its refinement around depth discontinuity and featureless areas,” inProceedings of IEEE International Geoscience and Remote Sensing Symposium (IEEE, 2010),pp 4576–4579.
[Crossref]

L. J. Kozlowski and W. F. Kosonocky, “Infrared detector arrays” in Handbook of Optics, 3rd edition, M. Bass, editor (McGraw-Hill, 2009), Volume II, Chapter 33.

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (10)

Fig. 1
Fig. 1 Architecture of a staggered TDI imager. (a) Scanning Imaging with a staggered TDI detector. (b) TDI focal plane layout with offset imaging arrays.
Fig. 2
Fig. 2 A TIR image sub-block taken by a staggered TDI airborne scanner. The image is dramtically degraded by instantaneous geometric distortion. Edge jitter is evident in the image. (a) The TIR image raw data. (b) The zoom-in sub-block of the area in the red box of the left image.
Fig. 3
Fig. 3 MTF loss due to degradation of motion displacement
Fig. 4
Fig. 4 The displacement estimation and realignment of two adjacent scanning lines.
Fig. 5
Fig. 5 The realignment residual VS number of iterations of two adjacent scanning lines with 2.0 pixel displacement
Fig. 6
Fig. 6 Simulation validation experiment with AF target image. (a) The degradation image with a sine pattern displacement along the scanning direction and blurring. (b) The restored result using the proposed CI method. (c) and (d) represent the zoom of ROI image blocks marked with a red box in (a) and (b), respectively. (e) The blue solid line is the true displacement vector in (a), and the red line is the displacement estimatedion result.
Fig. 7
Fig. 7 An airborne TIR image and the restored result. (a) The staggered TDI thermal raw image. (b) The restoration result using the proposed CI method. (c) The zoom sub-image in (a) marked with red box #1. (d) The corresponding restored result in (b) marked with red box #2. (e) The difference map between (c) and (d). (f) The zoom sub-image in (a) marked with red box #3. (g) The corresponding restored result in (b) marked with red box #4. (h) The difference map between (f) and (g).
Fig. 8
Fig. 8 The displacement estimation of the TIR raw image presented in Fig. 7(a)
Fig. 9
Fig. 9 The image intensity profiles comparison of raw image with that of realignment image and restoration image. (a) Image intensity profiles of dotted red line #1 and #1' in Figs. 7(a) and 7(b) and intensity profile of odd-rows image. (b) Image intensity profiles of dotted red line #2 and #2' in Figs. 7(a) and 7(b) and intensity profile of realignment image
Fig. 10
Fig. 10 The normalized spatial frequency curves of raw image and restored image. The higher frequency components in the dotted circle resulting from non-uniform image distortion

Equations (7)

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

I ( r , c ) = k = 1 N i k
s = 0 t s v ( t ) d t
M T F ( f ) = | sin c ( π f d ) |
{ g t i = D t i M t i f p s f s y s + n t i ( i = 1 , 2 ) p s f s y s = p s f o p t p s f det p s f m o t i o n p s f t h
1 [ { w g i } * { w g i + 1 } | { w g i } * { w g i + 1 } | ] r ( n + n )
g ( n n ) e j ω n G ( ω )
{ f ^ = arg min f i = 1 2 | | k f g t i | | 2 + λ 1 | D f | + λ 2 | D 2 f | k ^ = arg min k i = 1 2 | | k f g t i | | 2 + r e g ( k )

Metrics