Abstract

We present a superresolution image reconstruction from a sequence of aliased imagery. The subpixel shifts (displacement) among the images are unknown due to the uncontrolled natural jitter of the imager. A correlation method is utilized to estimate subpixel shifts between each low-resolution aliased image with respect to a reference image. An error-energy reduction algorithm is derived to reconstruct the high-resolution alias-free output image. The main feature of this proposed error-energy reduction algorithm is that we treat the spatial samples from low-resolution images that possess unknown and irregular (uncontrolled) subpixel shifts as a set of constraints to populate an oversampled (sampled above the desired output bandwidth) processing array. The estimated subpixel locations of these samples and their values constitute a spatial domain constraint. Furthermore, the bandwidth of the alias-free image (or the sensor imposed bandwidth) is the criterion used as a spatial frequency domain constraint on the oversampled processing array. The results of testing the proposed algorithm on the simulated low- resolution forward-looking infrared (FLIR) images, real-world FLIR images, and visible images are provided. A comparison of the proposed algorithm with a standard interpolation algorithm for processing the simulated low-resolution FLIR images is also provided.

© 2006 Optical Society of America

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    [CrossRef]

2005 (1)

M. Ben-Ezra, A. Zomet, and S. K. Nayar, "Video superresolution using controlled subpixel detector shifts," IEEE Trans. Pattern Anal. Mach. Intell. 27, 977-987 (2005).
[CrossRef]

2004 (4)

Z. Zalevsky, N. Shamir, and D. Mendlovic, "Geometrical superresolution in infrared sensor: experimental verification," Opt. Eng. 43, 1401-1406 (2004).
[CrossRef]

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe superresolution," IEEE Trans. Image Process. 13, 1327-1344 (2004).
[CrossRef]

K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

S. S. Young, "Alias-free image subsampling using Fourier-based windowing methods," Opt. Eng. 43, 843-855 (2004).
[CrossRef]

2003 (4)

P. Vandewalle, S. Susstrunk, and M. Vetterli, "Superresolution images reconstruction from aliased images," in Visual Communications and Image Processing,Proc. SPIE 5150, 1398-1405 (2003).
[CrossRef]

D. Rajan and S. Chaudhuri, "Simultaneous estimation of superresolved scene and depth map from low resolution defocused observations," IEEE Trans. Pattern Anal. Mach. Intell. 25, 1102-1115 (2003).
[CrossRef]

E. S. Lee and M. G. Kang, "Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration," IEEE Trans. Image Process. 12, 826-837 (2003).
[CrossRef]

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

2002 (4)

H. Foroosh, J. B. Zerubia, and M. Berthod, "Extension of phase correlation to subpixel registration," IEEE Trans. Image Process. 11, 188-200 (2002).
[CrossRef]

S. Lertrattanapanich and N. K. Bose, "High resolution image formation from low resolution frams using Delaunay Triangulation," IEEE Trans. Image Process. 11, 1427-1441 (2002).
[CrossRef]

R. A. Gonsalves and F. Khaghani, "Superresolution based on low-resolution, warped images," in Applications of Digital Image Processing XXV,Proc. SPIE 4790, 11-20 (2002).
[CrossRef]

J. M. Schuler, J. G. Howard, P. Warren, and D. Scribner, "TARID-based image superresolution," in Infrared and Passive Millimeter-Wave Imaging Systems; Design, Analysis, Modeling, and Testing, Proc SPIE 4719, 247-254 (2002).
[CrossRef]

2001 (2)

M. Elad and Y. Hel-Or, "A fast superresolution reconstruction algorithm for pure translational motion and common space-invariant blur," IEEE Trans. Image Process. 10, 1187-1193 (2001).
[CrossRef]

H. S. Stone, M. T. Orchard, E.-C. Chang, and S. A. Martucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sens. 39, 2235-2243 (2001).
[CrossRef]

2000 (3)

C. L. L. Hendriks and L. J. van Vliet, "Improving resolution to reduce aliasing in an undersampled image sequence," in Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications,Proc. SPIE 3965, 214-222 (2000).
[CrossRef]

M. C. Chiang and T. E. Boult, "Efficient superresolution via image warping," Image Vis. Comput. 18, 761-771 (2000).
[CrossRef]

M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, "Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames," IEEE Trans. Instrum. Meas. 49, 915-923 (2000).
[CrossRef]

1999 (1)

F. M. Candocia and J. C. Principe, "Superresolution of images based on local correlations," IEEE Trans. Neural Netw. 10, 372-380 (1999).
[CrossRef]

1998 (1)

S. Borman and R. L. Stevenson, "Superresolution from image sequences--a review," Proc. 1998 Midwest Symp. Circuits and Systems (IEEE, 1998), pp. 374-378.

1997 (2)

A. J. Patti, M. I. Sezan, and A. M. Tekalp, "Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time," IEEE Trans. Image Process. 6, 1064-1076 (1997).
[CrossRef]

R. C. Hardie, K. J. Barnard, and E. E. Armstrong, "Joint MAP registration and high-resolution image estimation using a sequence of undersampled images," IEEE Trans. Image Process. 6, 1621-1633 (1997).
[CrossRef]

1996 (1)

R. R. Schulz and R. L. Stevenson, "Extraction of high-resolution frames from video sequences," IEEE Trans. Image Process. 5, 996-1011 (1996).
[CrossRef]

1993 (1)

S. P. Kim and W. Y. Su, "Subpixel accuracy image registration by spectrum cancellation," Proceedings of ICASSP-93--1993 IEEE International Conference on Acoustics, Speech, and Signal Processing (1993), Vol. 5, pp. 153-156.

1992 (1)

H. Ur and D. Gross, "Improved resolution from subpixel shifted pictures," CVGIP: Graph. Models Image Process. 54, 181-186 (1992).
[CrossRef]

1989 (1)

1988 (1)

M. Bierling, "Displacement estimation by hierarchical blockmatching," in Visual Communications and Image Processing '88,Proc. SPIE 1001, 942-951 (1988).

1987 (2)

D. J. Heeger, "Model for the extraction of image flow," J. Opt. Soc. Am. A 4, 1455-1471 (1987).

D. T. Sandwell, "Biharmonic spline interpolation of Geo-3 and Seasat altimeter data," Geophys. Res. Lett. 14, 139-142 (1987).

1985 (1)

R. P. Kleihorst, R. L. Lagendijk, and J. Biemond, "Noise reduction of image sequences using motion compensation and signal decomposition," IEEE Trans. Image Processing 4, 274-284 (1985).
[CrossRef]

1981 (1)

B. K. P. Horn and B. G. Schunk, "Determining optical flow," Artif. Intell. 17, 185-203 (1981).
[CrossRef]

1975 (2)

A. Papoulis, "A new algorithm in spectral analysis and band-limited extrapolation," IEEE Trans. on Circuits Syst. 22, 735-742 (1975).
[CrossRef]

P. De Santis and F. Gori, "On an iterative method for superresolution," Opt. Acta 22, 691-695 (1975).

1974 (1)

R. W. Gerchberg, "Superresolution through error energy reduction," Opt. Acta 21, 709-720 (1974).

Alam, M. S.

M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, "Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames," IEEE Trans. Instrum. Meas. 49, 915-923 (2000).
[CrossRef]

Armstrong, E. E.

R. C. Hardie, K. J. Barnard, and E. E. Armstrong, "Joint MAP registration and high-resolution image estimation using a sequence of undersampled images," IEEE Trans. Image Process. 6, 1621-1633 (1997).
[CrossRef]

Barnard, K. J.

R. C. Hardie, K. J. Barnard, and E. E. Armstrong, "Joint MAP registration and high-resolution image estimation using a sequence of undersampled images," IEEE Trans. Image Process. 6, 1621-1633 (1997).
[CrossRef]

Ben-Ezra, M.

M. Ben-Ezra, A. Zomet, and S. K. Nayar, "Video superresolution using controlled subpixel detector shifts," IEEE Trans. Pattern Anal. Mach. Intell. 27, 977-987 (2005).
[CrossRef]

Bergen, J. R.

J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.

Bertero, M.

M. Bertero and C. Demol, "Superresolution by data inversion," Progress In Optics, Vol. 36 (Elsevier North-Holland, 1996), pp. 129-178.

Berthod, M.

H. Foroosh, J. B. Zerubia, and M. Berthod, "Extension of phase correlation to subpixel registration," IEEE Trans. Image Process. 11, 188-200 (2002).
[CrossRef]

Biemond, J.

R. P. Kleihorst, R. L. Lagendijk, and J. Biemond, "Noise reduction of image sequences using motion compensation and signal decomposition," IEEE Trans. Image Processing 4, 274-284 (1985).
[CrossRef]

Bierling, M.

M. Bierling, "Displacement estimation by hierarchical blockmatching," in Visual Communications and Image Processing '88,Proc. SPIE 1001, 942-951 (1988).

Bognar, J. G.

M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, "Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames," IEEE Trans. Instrum. Meas. 49, 915-923 (2000).
[CrossRef]

Borman, S.

S. Borman and R. L. Stevenson, "Superresolution from image sequences--a review," Proc. 1998 Midwest Symp. Circuits and Systems (IEEE, 1998), pp. 374-378.

Bose, N. K.

S. Lertrattanapanich and N. K. Bose, "High resolution image formation from low resolution frams using Delaunay Triangulation," IEEE Trans. Image Process. 11, 1427-1441 (2002).
[CrossRef]

N. K. Bose, "Superresolution from image sequence," Proceedings of IEEE International Conference on Image Processing 2004 (IEEE, 2004), pp. 81-86.

Boult, T. E.

M. C. Chiang and T. E. Boult, "Efficient superresolution via image warping," Image Vis. Comput. 18, 761-771 (2000).
[CrossRef]

Burt, P. J.

J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.

Candocia, F. M.

F. M. Candocia and J. C. Principe, "Superresolution of images based on local correlations," IEEE Trans. Neural Netw. 10, 372-380 (1999).
[CrossRef]

Chang, E.-C.

H. S. Stone, M. T. Orchard, E.-C. Chang, and S. A. Martucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sens. 39, 2235-2243 (2001).
[CrossRef]

Chaudhuri, S.

D. Rajan and S. Chaudhuri, "Simultaneous estimation of superresolved scene and depth map from low resolution defocused observations," IEEE Trans. Pattern Anal. Mach. Intell. 25, 1102-1115 (2003).
[CrossRef]

Chiang, M. C.

M. C. Chiang and T. E. Boult, "Efficient superresolution via image warping," Image Vis. Comput. 18, 761-771 (2000).
[CrossRef]

De Santis, P.

P. De Santis and F. Gori, "On an iterative method for superresolution," Opt. Acta 22, 691-695 (1975).

Demol, C.

M. Bertero and C. Demol, "Superresolution by data inversion," Progress In Optics, Vol. 36 (Elsevier North-Holland, 1996), pp. 129-178.

Driggers, R. G.

K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

Elad, M.

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe superresolution," IEEE Trans. Image Process. 13, 1327-1344 (2004).
[CrossRef]

M. Elad and Y. Hel-Or, "A fast superresolution reconstruction algorithm for pure translational motion and common space-invariant blur," IEEE Trans. Image Process. 10, 1187-1193 (2001).
[CrossRef]

Farsiu, S.

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe superresolution," IEEE Trans. Image Process. 13, 1327-1344 (2004).
[CrossRef]

Foroosh, H.

H. Foroosh, J. B. Zerubia, and M. Berthod, "Extension of phase correlation to subpixel registration," IEEE Trans. Image Process. 11, 188-200 (2002).
[CrossRef]

Gerchberg, R. W.

R. W. Gerchberg, "Superresolution through error energy reduction," Opt. Acta 21, 709-720 (1974).

Gonsalves, R. A.

R. A. Gonsalves and F. Khaghani, "Superresolution based on low-resolution, warped images," in Applications of Digital Image Processing XXV,Proc. SPIE 4790, 11-20 (2002).
[CrossRef]

Gori, F.

P. De Santis and F. Gori, "On an iterative method for superresolution," Opt. Acta 22, 691-695 (1975).

Gross, D.

H. Ur and D. Gross, "Improved resolution from subpixel shifted pictures," CVGIP: Graph. Models Image Process. 54, 181-186 (1992).
[CrossRef]

Hanna, K.

J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.

Hardie, R. C.

M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, "Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames," IEEE Trans. Instrum. Meas. 49, 915-923 (2000).
[CrossRef]

R. C. Hardie, K. J. Barnard, and E. E. Armstrong, "Joint MAP registration and high-resolution image estimation using a sequence of undersampled images," IEEE Trans. Image Process. 6, 1621-1633 (1997).
[CrossRef]

Heeger, D. J.

Hel-Or, Y.

M. Elad and Y. Hel-Or, "A fast superresolution reconstruction algorithm for pure translational motion and common space-invariant blur," IEEE Trans. Image Process. 10, 1187-1193 (2001).
[CrossRef]

Hendriks, C. L. L.

C. L. L. Hendriks and L. J. van Vliet, "Improving resolution to reduce aliasing in an undersampled image sequence," in Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications,Proc. SPIE 3965, 214-222 (2000).
[CrossRef]

Hingorari, R.

J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.

Horn, B. K. P.

B. K. P. Horn and B. G. Schunk, "Determining optical flow," Artif. Intell. 17, 185-203 (1981).
[CrossRef]

Howard, J. G.

J. M. Schuler, J. G. Howard, P. Warren, and D. Scribner, "TARID-based image superresolution," in Infrared and Passive Millimeter-Wave Imaging Systems; Design, Analysis, Modeling, and Testing, Proc SPIE 4719, 247-254 (2002).
[CrossRef]

Huang, T. S.

R. Y. Tsai and T. S. Huang, "Multiple frame image restoration and registration," in Advances in Computer Vision and Image Processing (JAI Press Inc., 1984), pp. 317-339.

Irani, M.

M. Irani and S. Peleg, "Image sequence enhancement using multiple motions analysis," Proceedings of 1992 IEEE Computer Society Conference on Computer Vision and Pattern Analysis (IEEE, 1992), pp. 216-221.

Jeanne, P.

J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.

Kang, M. G.

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

E. S. Lee and M. G. Kang, "Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration," IEEE Trans. Image Process. 12, 826-837 (2003).
[CrossRef]

Katsaggelos, A. K.

J. Mateos, M. Vega, R. Molina, and A. K. Katsaggelos, "Baysian image estimation from an incomplete set of blurred, undersampled low resolution images," Proceedings Lecture Notes in Computer Science 2652, Pattern Recognition and Image Analysis (IEEE, 2003), pp. 538-546.

Khaghani, F.

R. A. Gonsalves and F. Khaghani, "Superresolution based on low-resolution, warped images," in Applications of Digital Image Processing XXV,Proc. SPIE 4790, 11-20 (2002).
[CrossRef]

Kim, S. P.

S. P. Kim and W. Y. Su, "Subpixel accuracy image registration by spectrum cancellation," Proceedings of ICASSP-93--1993 IEEE International Conference on Acoustics, Speech, and Signal Processing (1993), Vol. 5, pp. 153-156.

Kleihorst, R. P.

R. P. Kleihorst, R. L. Lagendijk, and J. Biemond, "Noise reduction of image sequences using motion compensation and signal decomposition," IEEE Trans. Image Processing 4, 274-284 (1985).
[CrossRef]

Krapels, K.

K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

Lagendijk, R. L.

R. P. Kleihorst, R. L. Lagendijk, and J. Biemond, "Noise reduction of image sequences using motion compensation and signal decomposition," IEEE Trans. Image Processing 4, 274-284 (1985).
[CrossRef]

Lee, E. S.

E. S. Lee and M. G. Kang, "Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration," IEEE Trans. Image Process. 12, 826-837 (2003).
[CrossRef]

Lertrattanapanich, S.

S. Lertrattanapanich and N. K. Bose, "High resolution image formation from low resolution frams using Delaunay Triangulation," IEEE Trans. Image Process. 11, 1427-1441 (2002).
[CrossRef]

Martucci, S. A.

H. S. Stone, M. T. Orchard, E.-C. Chang, and S. A. Martucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sens. 39, 2235-2243 (2001).
[CrossRef]

Mateos, J.

J. Mateos, M. Vega, R. Molina, and A. K. Katsaggelos, "Baysian image estimation from an incomplete set of blurred, undersampled low resolution images," Proceedings Lecture Notes in Computer Science 2652, Pattern Recognition and Image Analysis (IEEE, 2003), pp. 538-546.

Mendlovic, D.

Z. Zalevsky, N. Shamir, and D. Mendlovic, "Geometrical superresolution in infrared sensor: experimental verification," Opt. Eng. 43, 1401-1406 (2004).
[CrossRef]

Milanfar, P.

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe superresolution," IEEE Trans. Image Process. 13, 1327-1344 (2004).
[CrossRef]

Molina, R.

J. Mateos, M. Vega, R. Molina, and A. K. Katsaggelos, "Baysian image estimation from an incomplete set of blurred, undersampled low resolution images," Proceedings Lecture Notes in Computer Science 2652, Pattern Recognition and Image Analysis (IEEE, 2003), pp. 538-546.

Murrill, S.

K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

Nayar, S. K.

M. Ben-Ezra, A. Zomet, and S. K. Nayar, "Video superresolution using controlled subpixel detector shifts," IEEE Trans. Pattern Anal. Mach. Intell. 27, 977-987 (2005).
[CrossRef]

Orchard, M. T.

H. S. Stone, M. T. Orchard, E.-C. Chang, and S. A. Martucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sens. 39, 2235-2243 (2001).
[CrossRef]

Oskoui, P.

Papoulis, A.

A. Papoulis, "A new algorithm in spectral analysis and band-limited extrapolation," IEEE Trans. on Circuits Syst. 22, 735-742 (1975).
[CrossRef]

Park, M. K.

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

Patti, A. J.

A. J. Patti, M. I. Sezan, and A. M. Tekalp, "Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time," IEEE Trans. Image Process. 6, 1064-1076 (1997).
[CrossRef]

Peleg, S.

M. Irani and S. Peleg, "Image sequence enhancement using multiple motions analysis," Proceedings of 1992 IEEE Computer Society Conference on Computer Vision and Pattern Analysis (IEEE, 1992), pp. 216-221.

J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.

Principe, J. C.

F. M. Candocia and J. C. Principe, "Superresolution of images based on local correlations," IEEE Trans. Neural Netw. 10, 372-380 (1999).
[CrossRef]

Rajan, D.

D. Rajan and S. Chaudhuri, "Simultaneous estimation of superresolved scene and depth map from low resolution defocused observations," IEEE Trans. Pattern Anal. Mach. Intell. 25, 1102-1115 (2003).
[CrossRef]

Robinson, M. D.

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe superresolution," IEEE Trans. Image Process. 13, 1327-1344 (2004).
[CrossRef]

Sandwell, D. T.

D. T. Sandwell, "Biharmonic spline interpolation of Geo-3 and Seasat altimeter data," Geophys. Res. Lett. 14, 139-142 (1987).

Sbaiz, L.

P. Vandewalle, L. Sbaiz, J. Vandewalle, and M. Vetterli, "How to take advantage of aliasing in bandlimited signals," Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2004), pp. 948-951.

Schuler, J.

K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

Schuler, J. M.

J. M. Schuler, J. G. Howard, P. Warren, and D. Scribner, "TARID-based image superresolution," in Infrared and Passive Millimeter-Wave Imaging Systems; Design, Analysis, Modeling, and Testing, Proc SPIE 4719, 247-254 (2002).
[CrossRef]

J. M. Schuler and D. A. Scribner, "Dynamic sampling, resolution enhancement, and superresolution," in Analysis of Sampled Imaging Systems, R. H. Vollmerhausen and R. G. Driggers, eds. (SPIE Press , 2000), pp. 125-138.

Schulz, R. R.

R. R. Schulz and R. L. Stevenson, "Extraction of high-resolution frames from video sequences," IEEE Trans. Image Process. 5, 996-1011 (1996).
[CrossRef]

Schunk, B. G.

B. K. P. Horn and B. G. Schunk, "Determining optical flow," Artif. Intell. 17, 185-203 (1981).
[CrossRef]

Scribner, D.

J. M. Schuler, J. G. Howard, P. Warren, and D. Scribner, "TARID-based image superresolution," in Infrared and Passive Millimeter-Wave Imaging Systems; Design, Analysis, Modeling, and Testing, Proc SPIE 4719, 247-254 (2002).
[CrossRef]

Scribner, D. A.

J. M. Schuler and D. A. Scribner, "Dynamic sampling, resolution enhancement, and superresolution," in Analysis of Sampled Imaging Systems, R. H. Vollmerhausen and R. G. Driggers, eds. (SPIE Press , 2000), pp. 125-138.

Sezan, M. I.

A. J. Patti, M. I. Sezan, and A. M. Tekalp, "Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time," IEEE Trans. Image Process. 6, 1064-1076 (1997).
[CrossRef]

Shamir, N.

Z. Zalevsky, N. Shamir, and D. Mendlovic, "Geometrical superresolution in infrared sensor: experimental verification," Opt. Eng. 43, 1401-1406 (2004).
[CrossRef]

Stark, H.

Stevenson, R. L.

S. Borman and R. L. Stevenson, "Superresolution from image sequences--a review," Proc. 1998 Midwest Symp. Circuits and Systems (IEEE, 1998), pp. 374-378.

R. R. Schulz and R. L. Stevenson, "Extraction of high-resolution frames from video sequences," IEEE Trans. Image Process. 5, 996-1011 (1996).
[CrossRef]

Stone, H. S.

H. S. Stone, M. T. Orchard, E.-C. Chang, and S. A. Martucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sens. 39, 2235-2243 (2001).
[CrossRef]

Su, W. Y.

S. P. Kim and W. Y. Su, "Subpixel accuracy image registration by spectrum cancellation," Proceedings of ICASSP-93--1993 IEEE International Conference on Acoustics, Speech, and Signal Processing (1993), Vol. 5, pp. 153-156.

Susstrunk, S.

P. Vandewalle, S. Susstrunk, and M. Vetterli, "Superresolution images reconstruction from aliased images," in Visual Communications and Image Processing,Proc. SPIE 5150, 1398-1405 (2003).
[CrossRef]

Tekalp, A. M.

A. J. Patti, M. I. Sezan, and A. M. Tekalp, "Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time," IEEE Trans. Image Process. 6, 1064-1076 (1997).
[CrossRef]

Thielke, M.

K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

Tsai, R. Y.

R. Y. Tsai and T. S. Huang, "Multiple frame image restoration and registration," in Advances in Computer Vision and Image Processing (JAI Press Inc., 1984), pp. 317-339.

Ur, H.

H. Ur and D. Gross, "Improved resolution from subpixel shifted pictures," CVGIP: Graph. Models Image Process. 54, 181-186 (1992).
[CrossRef]

van Vliet, L. J.

C. L. L. Hendriks and L. J. van Vliet, "Improving resolution to reduce aliasing in an undersampled image sequence," in Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications,Proc. SPIE 3965, 214-222 (2000).
[CrossRef]

Vandewalle, J.

P. Vandewalle, L. Sbaiz, J. Vandewalle, and M. Vetterli, "How to take advantage of aliasing in bandlimited signals," Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2004), pp. 948-951.

Vandewalle, P.

P. Vandewalle, S. Susstrunk, and M. Vetterli, "Superresolution images reconstruction from aliased images," in Visual Communications and Image Processing,Proc. SPIE 5150, 1398-1405 (2003).
[CrossRef]

P. Vandewalle, L. Sbaiz, J. Vandewalle, and M. Vetterli, "How to take advantage of aliasing in bandlimited signals," Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2004), pp. 948-951.

Vega, M.

J. Mateos, M. Vega, R. Molina, and A. K. Katsaggelos, "Baysian image estimation from an incomplete set of blurred, undersampled low resolution images," Proceedings Lecture Notes in Computer Science 2652, Pattern Recognition and Image Analysis (IEEE, 2003), pp. 538-546.

Vetterli, M.

P. Vandewalle, S. Susstrunk, and M. Vetterli, "Superresolution images reconstruction from aliased images," in Visual Communications and Image Processing,Proc. SPIE 5150, 1398-1405 (2003).
[CrossRef]

P. Vandewalle, L. Sbaiz, J. Vandewalle, and M. Vetterli, "How to take advantage of aliasing in bandlimited signals," Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2004), pp. 948-951.

Warren, P.

J. M. Schuler, J. G. Howard, P. Warren, and D. Scribner, "TARID-based image superresolution," in Infrared and Passive Millimeter-Wave Imaging Systems; Design, Analysis, Modeling, and Testing, Proc SPIE 4719, 247-254 (2002).
[CrossRef]

Yasuda, B. J.

M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, "Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames," IEEE Trans. Instrum. Meas. 49, 915-923 (2000).
[CrossRef]

Young, S. S.

S. S. Young, "Alias-free image subsampling using Fourier-based windowing methods," Opt. Eng. 43, 843-855 (2004).
[CrossRef]

K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

Zalevsky, Z.

Z. Zalevsky, N. Shamir, and D. Mendlovic, "Geometrical superresolution in infrared sensor: experimental verification," Opt. Eng. 43, 1401-1406 (2004).
[CrossRef]

Zerubia, J. B.

H. Foroosh, J. B. Zerubia, and M. Berthod, "Extension of phase correlation to subpixel registration," IEEE Trans. Image Process. 11, 188-200 (2002).
[CrossRef]

Zomet, A.

M. Ben-Ezra, A. Zomet, and S. K. Nayar, "Video superresolution using controlled subpixel detector shifts," IEEE Trans. Pattern Anal. Mach. Intell. 27, 977-987 (2005).
[CrossRef]

Artif. Intell. (1)

B. K. P. Horn and B. G. Schunk, "Determining optical flow," Artif. Intell. 17, 185-203 (1981).
[CrossRef]

CVGIP: Graph. Models Image Process. (1)

H. Ur and D. Gross, "Improved resolution from subpixel shifted pictures," CVGIP: Graph. Models Image Process. 54, 181-186 (1992).
[CrossRef]

Geophys. Res. Lett. (1)

D. T. Sandwell, "Biharmonic spline interpolation of Geo-3 and Seasat altimeter data," Geophys. Res. Lett. 14, 139-142 (1987).

IEEE Signal Process. Mag. (1)

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

IEEE Trans. Geosci. Remote Sens. (1)

H. S. Stone, M. T. Orchard, E.-C. Chang, and S. A. Martucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sens. 39, 2235-2243 (2001).
[CrossRef]

IEEE Trans. Image Process. (8)

S. Lertrattanapanich and N. K. Bose, "High resolution image formation from low resolution frams using Delaunay Triangulation," IEEE Trans. Image Process. 11, 1427-1441 (2002).
[CrossRef]

H. Foroosh, J. B. Zerubia, and M. Berthod, "Extension of phase correlation to subpixel registration," IEEE Trans. Image Process. 11, 188-200 (2002).
[CrossRef]

A. J. Patti, M. I. Sezan, and A. M. Tekalp, "Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time," IEEE Trans. Image Process. 6, 1064-1076 (1997).
[CrossRef]

R. R. Schulz and R. L. Stevenson, "Extraction of high-resolution frames from video sequences," IEEE Trans. Image Process. 5, 996-1011 (1996).
[CrossRef]

R. C. Hardie, K. J. Barnard, and E. E. Armstrong, "Joint MAP registration and high-resolution image estimation using a sequence of undersampled images," IEEE Trans. Image Process. 6, 1621-1633 (1997).
[CrossRef]

M. Elad and Y. Hel-Or, "A fast superresolution reconstruction algorithm for pure translational motion and common space-invariant blur," IEEE Trans. Image Process. 10, 1187-1193 (2001).
[CrossRef]

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe superresolution," IEEE Trans. Image Process. 13, 1327-1344 (2004).
[CrossRef]

E. S. Lee and M. G. Kang, "Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration," IEEE Trans. Image Process. 12, 826-837 (2003).
[CrossRef]

IEEE Trans. Image Processing (1)

R. P. Kleihorst, R. L. Lagendijk, and J. Biemond, "Noise reduction of image sequences using motion compensation and signal decomposition," IEEE Trans. Image Processing 4, 274-284 (1985).
[CrossRef]

IEEE Trans. Instrum. Meas. (1)

M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, "Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames," IEEE Trans. Instrum. Meas. 49, 915-923 (2000).
[CrossRef]

IEEE Trans. Neural Netw. (1)

F. M. Candocia and J. C. Principe, "Superresolution of images based on local correlations," IEEE Trans. Neural Netw. 10, 372-380 (1999).
[CrossRef]

IEEE Trans. on Circuits Syst. (1)

A. Papoulis, "A new algorithm in spectral analysis and band-limited extrapolation," IEEE Trans. on Circuits Syst. 22, 735-742 (1975).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell. (2)

D. Rajan and S. Chaudhuri, "Simultaneous estimation of superresolved scene and depth map from low resolution defocused observations," IEEE Trans. Pattern Anal. Mach. Intell. 25, 1102-1115 (2003).
[CrossRef]

M. Ben-Ezra, A. Zomet, and S. K. Nayar, "Video superresolution using controlled subpixel detector shifts," IEEE Trans. Pattern Anal. Mach. Intell. 27, 977-987 (2005).
[CrossRef]

Image Vis. Comput. (1)

M. C. Chiang and T. E. Boult, "Efficient superresolution via image warping," Image Vis. Comput. 18, 761-771 (2000).
[CrossRef]

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Opt. Acta (2)

R. W. Gerchberg, "Superresolution through error energy reduction," Opt. Acta 21, 709-720 (1974).

P. De Santis and F. Gori, "On an iterative method for superresolution," Opt. Acta 22, 691-695 (1975).

Opt. Eng. (2)

Z. Zalevsky, N. Shamir, and D. Mendlovic, "Geometrical superresolution in infrared sensor: experimental verification," Opt. Eng. 43, 1401-1406 (2004).
[CrossRef]

S. S. Young, "Alias-free image subsampling using Fourier-based windowing methods," Opt. Eng. 43, 843-855 (2004).
[CrossRef]

Proc SPIE (1)

J. M. Schuler, J. G. Howard, P. Warren, and D. Scribner, "TARID-based image superresolution," in Infrared and Passive Millimeter-Wave Imaging Systems; Design, Analysis, Modeling, and Testing, Proc SPIE 4719, 247-254 (2002).
[CrossRef]

Proc. SPIE (5)

C. L. L. Hendriks and L. J. van Vliet, "Improving resolution to reduce aliasing in an undersampled image sequence," in Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications,Proc. SPIE 3965, 214-222 (2000).
[CrossRef]

R. A. Gonsalves and F. Khaghani, "Superresolution based on low-resolution, warped images," in Applications of Digital Image Processing XXV,Proc. SPIE 4790, 11-20 (2002).
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K. Krapels, R. G. Driggers, S. Murrill, J. Schuler, M. Thielke, and S. S. Young, "Superresolution performance for undersampled imagers," in Defense and Security Symposium (Formerly AeroSense),Proc. SPIE 5407, 139-149 (2004).
[CrossRef]

P. Vandewalle, S. Susstrunk, and M. Vetterli, "Superresolution images reconstruction from aliased images," in Visual Communications and Image Processing,Proc. SPIE 5150, 1398-1405 (2003).
[CrossRef]

SPIE Press (1)

J. M. Schuler and D. A. Scribner, "Dynamic sampling, resolution enhancement, and superresolution," in Analysis of Sampled Imaging Systems, R. H. Vollmerhausen and R. G. Driggers, eds. (SPIE Press , 2000), pp. 125-138.

Other (10)

S. Borman and R. L. Stevenson, "Superresolution from image sequences--a review," Proc. 1998 Midwest Symp. Circuits and Systems (IEEE, 1998), pp. 374-378.

M. Bertero and C. Demol, "Superresolution by data inversion," Progress In Optics, Vol. 36 (Elsevier North-Holland, 1996), pp. 129-178.

J. R. Bergen, P. J. Burt, K. Hanna, R. Hingorari, P. Jeanne, and S. Peleg, "Dynamic multiple-motion computation, inArtificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, Y. A. Feldman and A. Bruckstein, eds. (Elsevier, 1991), pp. 147-156.

S. P. Kim and W. Y. Su, "Subpixel accuracy image registration by spectrum cancellation," Proceedings of ICASSP-93--1993 IEEE International Conference on Acoustics, Speech, and Signal Processing (1993), Vol. 5, pp. 153-156.

N. K. Bose, "Superresolution from image sequence," Proceedings of IEEE International Conference on Image Processing 2004 (IEEE, 2004), pp. 81-86.

P. Vandewalle, L. Sbaiz, J. Vandewalle, and M. Vetterli, "How to take advantage of aliasing in bandlimited signals," Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2004), pp. 948-951.

M. Irani and S. Peleg, "Image sequence enhancement using multiple motions analysis," Proceedings of 1992 IEEE Computer Society Conference on Computer Vision and Pattern Analysis (IEEE, 1992), pp. 216-221.

R. Y. Tsai and T. S. Huang, "Multiple frame image restoration and registration," in Advances in Computer Vision and Image Processing (JAI Press Inc., 1984), pp. 317-339.

J. Mateos, M. Vega, R. Molina, and A. K. Katsaggelos, "Baysian image estimation from an incomplete set of blurred, undersampled low resolution images," Proceedings Lecture Notes in Computer Science 2652, Pattern Recognition and Image Analysis (IEEE, 2003), pp. 538-546.

http://www.cns.nvu.edu/∼david/ftp/registration/.

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Figures (10)

Fig. 1
Fig. 1

(a) Overview of the superresolution image reconstruction algorithm. (b) Subpixel shift estimation algorithm for 2D images.

Fig. 2
Fig. 2

An example of subpixel shift estimation from 16 frames. The numbers on the figure represent the names of frames. The subpixel shifts of each frame with respect to a reference frame are illustrated at their corresponding subpixel locations.

Fig. 3
Fig. 3

(a) Image acquisition model. (b) Factors that dictate the bandwidth of the measured target signature.

Fig. 4
Fig. 4

Bandwidth phenomenon in the superresolution image reconstruction algorithm.

Fig. 5
Fig. 5

(a) Error-energy reduction algorithm. (b) An example of error-energy reduction algorithm for 1D signals.

Fig. 6
Fig. 6

Simulated low-resolution FLIR images. (a) Original FLIR tank image. (b) Simulated high-resolution image. (c)–(f) Four simulated low-resolution images. (g) Simulated and correlation estimated subpixel shifts (the horizontal shift represents the first dimension shift and the vertical shift represents the second dimension shift). (h) Simulated and gradient estimated subpixel shifts. (i) One of the simulated low-resolution images. (j) One of the bilinear interpolated low-resolution images. (k) High-resolution output image by the standard interpolation method based on the gradient estimated subpixel shifts. (l) Superresolved image.

Fig. 7
Fig. 7

Fig. 6.Continued.

Fig. 7
Fig. 7

FLIR images of a foliage area. (a) One of the original low-resolution images. (b) One of the bilinear interpolated low-resolution images. (c) Superresolved image.

Fig. 8
Fig. 8

FLIR images of a pickup truck. (a) One of the bilinear interpolated low-resolution images. (b) Superresolved image.

Fig. 9
Fig. 9

Visible images. (a) Entire low-resolution test pattern image. (b) One of the bilinear interpolated image of a portion of the low-resolution image that is indicated from the box in (a). (c) Superresolved image of the same portion.

Equations (12)

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

f 2 ( x , y ) = f 1 ( x x s , y y s ) ,
G 12 ( k x ) = F 2 ( k x ) F 1 * ( k x ) ,
G ( k x ) = F ( k x ) H ( k x ) ,
B o = min ( B t , B s ) ,
g δ ( x ) = n = N N g ( x ) δ ( x x n ) = g ( x ) n = N N δ ( x x n ) .
G δ ( k x ) = 1 Δ x = N N G ( k x 2 π Δ x ) .
Δ x > 2 π B o ( Nyquist   sample   spacing ) .
p 1 ( x , y ) = { p ( x , y ) , 0 , ( x , y ) [ X p , Y p ] otherwise ,
P 2 ( k x , k y ) = P 1 ( k x , k y ) W p ( k x , k y ) ,
p 3 ( x , y ) = { p ( x , y ) , p 2 ( x , y ) , ( x , y ) [ X p , Y p ] otherwise .
e 2 n + 1 = ( x , y ) [ X p , Y p ] [ p 2 n + 1 ( x , y ) p ( x , y ) ] 2 .
SNR 2 n + 1 = 10 log 10 ( ( x , y ) [ X p , Y p ] [ p ( x , y ) ] 2 ( x , y ) [ X p , Y p ] [ p ( x , y ) p 2 n + 1 ( x , y ) ] 2 ) .

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