Abstract

Nonuniform exposures often affect imaging systems, e.g., owing to vignetting. Moreover, the sensor’s radiometric response may be nonlinear. These characteristics hinder photometric measurements. They are particularly annoying in image mosaicking, in which images are stitched to enhance the field of view. Mosaics suffer from seams stemming from radiometric inconsistencies between raw images. Prior methods feathered the seams but did not address their root cause. We handle these problems in a unified framework. We suggest a method for simultaneously estimating the radiometric response and the camera nonuniformity, based on a frame sequence acquired during camera motion. The estimated functions are then compensated for. This permits image mosaicking, in which no seams are apparent. There is no need to resort to dedicated seam-feathering methods. Fundamental ambiguities associated with this estimation problem are stated.

© 2005 Optical Society of America

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References

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  1. S. B. Kang, R. Weiss, “Can we calibrate a camera using an image of a flat, textureless Lambertian surface?” in Proceedings of European Conference on Computer Vision, (Springer, New York, 2000), Part 2, pp. 640–653.
  2. I. C. Khoo, M. V. Wood, M. Y. Shih, P. H. Chen, “Extremely nonlinear photosensitive liquid crystals for image sensing and sensor protection,” Opt. Express 4, 432–442 (1999).
    [CrossRef] [PubMed]
  3. N. Tabiryan, S. Nersisyan, “Liquid-crystal film eclipses the sun artificially,” Laser Focus World 38, 105–108 (2002).
  4. In different communities the terms mosaicing[5, 6] and mosaicking[7, 8, 9, 10] are used.
  5. D. Capel, A. Zisserman, “Automated mosaicing with super-resolution zoom,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1998), pp. 885–891.
  6. S. Peleg, M. Ben-Ezra, Y. Pritch, “Omnistereo: panoramic stereo imaging,” IEEE Trans. Pattern Anal. Mach. Intell. 23, 279–290 (2001).
    [CrossRef]
  7. R. Kwok, J. C. Curlander, S. Pang, “An automated system for mosaicking spaceborne SAR imagery,” Int. J. Remote Sens. 11, 209–223 (1990).
    [CrossRef]
  8. R. Eustice, O. Pizarro, H. Singh, J. Howland, “UWIT: Underwater Image Toolbox for optical image processing and mosaicking in MATLAB,” in Proceedings of IEEE International Symposium on Underwater Technology (IEEE Press, Piscataway, N.J., 2002), pp. 141–145.
  9. R. Garcia, J. Batlle, X. Cufi, J. Amat, “Positioning an underwater vehicle through image mosaicking,” in Proceedings of IEEE International Conference on Robotics and Automation (IEEE Press, Piscataway, N.J., 2001), Part 3, pp. 2779–2784.
  10. M. L. Duplaquet, “Building large image mosaics with invisible seam lines,” in Visual Information Processing VII, S. K. Park and R. D. Juday, eds., Proc. SPIE3387, 369–377 (1998).
  11. C. J. Lada, D. L. DePoy, K. M. Merrill, I. Gatley, “Infrared images of M17,” Astron. J. 374, 533–539 (1991).
    [CrossRef]
  12. L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
    [CrossRef]
  13. J. M. Uson, S. P. Boughn, J. R. Kuhn, “The central galaxy in Abell 2029: an old supergiant,” Science 250, 539–540 (1990).
    [CrossRef] [PubMed]
  14. A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
    [CrossRef]
  15. S. Negahdaripour, X. Xu, A. Khemene, Z. Awan, “3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROV’s/AUV’s and high-resolution sea-floor mapping,” in Proceedings of IEEE Workshop on Autonomous Underwater Vehicles (IEEE Press, Piscataway, N.J., 1998), pp. 191–200.
  16. M. Hansen, P. Anandan, K. Dana, G. van der Wal, P. Burt, “Real-time scene stabilization and mosaic construction,” in Proceedings of IEEE Workshop on Applications of Computer Vision (IEEE Press, Piscataway, N.J., 1994), pp. 54–62.
  17. E. M. Reynoso, G. M. Dubner, W. M. Goss, E. M. Arnal, “VLA observations of neutral hydrogen in the direction of Puppis A,” Astron. J. 110, 318–324 (1995).
    [CrossRef]
  18. P. J. Burt, E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graphics 2, 217–236 (1983).
    [CrossRef]
  19. A. Levin, A. Zomet, S. Peleg, Y. Weiss, “Seamless image stitching in the gradient domain,” in Proceedings of European Conference in Computer Vision (Springer, New York, 2004), Part IV, pp. 377–390.
  20. H. Y. Shum, R. Szeliski, “Systems and experiment paper: construction of panoramic image mosaics with global and local alignment,” Int. J. Comput. Vision 36, 101–130 (2000).
    [CrossRef]
  21. M. Aggarwal, N. Ahuja, “High dynamic range panoramic imaging,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 2–9.
  22. Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 17–24.
  23. Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing: high dynamic range in a wide field of view,” Int. J. Comput. Vision 53, 245–267 (2003).
    [CrossRef]
  24. P. E. Debevec, J. Malik, “Recovering high dynamic range radiance maps from photographs,” in Proceedings of SIGGRAPH 97 (Association for Computing Machinery, New York, 1997), pp. 369–378.
  25. S. Mann, R. W. Picard, “On being ‘undigital’ with digital cameras: extending dynamic range by combining differently exposed pictures,” in Proceedings of IS&T 48th Annual Conference (Society for Imaging Science and Technology, Springfield, Va., 1995), pp. 422–428.
  26. S. Mann, “Comparametric equations with practical applications in quantigraphic image processing,” IEEE Trans. Image Process. 9, 1389–1406 (2000).
    [CrossRef]
  27. T. Mitsunaga, S. K. Nayar, “Radiometric self calibration,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1999), Vol. I, pp. 374–380.
  28. S. J. Kim, M. Pollefeys, “Radiometric alignment of image sequences,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. I, pp. 645–652.
  29. J. Jia, C. K. Tang, “Image registration with global and local luminance alignment,” in Proceedings of IEEE Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2003), Vol. I, pp. 156–163.
  30. F. M. Candocia, “Jointly registering images in domain and range by piecewise linear comparametric analysis,” IEEE Trans. Image Process. 12, 409–419 (2003).
    [CrossRef]
  31. S. Mann, R. Mann, “Quantigraphic imaging: estimating the camera response and exposures from differently exposed images,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2001), Vol. 1, pp. 842–849.
  32. M. D. Grossberg, S. K. Nayar, “Determining the camera response from images: what is knowable?,” IEEE Trans. Pattern Anal. Mach. Intell. 25, 1455–1467 (2003).
    [CrossRef]
  33. P. Törle, “Scene-based correction of image sensor deficiencies,” MSc. thesis (Linköping Institute of Technology, Linköping, Sweden, 2003).
  34. R. C. Hardie, M. M. Hayat, E. Armstrong, B. Yasuda, “Scene-based nonuniformity correction with video sequences and registration,” Appl. Opt. 39, 1241–1250 (2000).
    [CrossRef]
  35. B. M. Ratliff, M. M. Hayat, J. S. Tyo, “Radiometrically accurate scene-based nonuniformity correction for array sensors,” J. Opt. Soc. Am. A 20, 1890–1899 (2003).
    [CrossRef]
  36. S. N. Torres, J. E. Pezoa, M. Hayat, “Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form,” Appl. Opt. 42, 5872–5881 (2003).
    [CrossRef] [PubMed]
  37. H. Farid, “Blind inverse gamma correction,” IEEE Trans. Image Process. 10, 1428–1433 (2001).
    [CrossRef]
  38. S. Lin, J. Gu, S. Yamazaki, H. Shum, “Radiometric calibration from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. II, pp. 938–946.
  39. S. Inoue, Video Microscopy (Plenum, New York, 1986). pp. 209–214.
  40. The radiometric response function is usually monotonically increasing. It monotonically decreases in negative films and in some camera modes.
  41. S. Hsu, H. S. Sawhney, R. Kumar, “Automated mosaics via topology inference,” IEEE Comput. Graphics Appl. 22, 44–54 (2002).
    [CrossRef]
  42. M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).
  43. R. K. Sharma, M. Pavel, “Multisensor image registration,” in Proceedings of the Society for Information Display (Society for Information Display, Playa del Ray, Calif., 1997), Vol. XXVIII, pp. 951–954 (1997).
  44. P. Thevenaz, M. Unser, “Optimization of mutual information for multiresolution image registration,” IEEE Trans. Image Process. 9, 2083–2099 (2000).
    [CrossRef]
  45. P. Viola, W. M. Wells, “Alignment by maximization of mutual information,” Int. J. Comput. Vision 24, 137–154 (1997).
    [CrossRef]
  46. We may avoid the apperance of trivial solution by expressing Eq. (15) in a matrix formulation. This is only one of the possible realizations of the requirement to avoid a nontrivial g. Another possibility is to fix the boundary range values of g.
  47. We placed the filter a few centimeters ahead of the lens. If the filter is placed right next to the lens, it affects the aperture properties[48] without producing spatially varying effects in the image.
  48. H. Farid, E. P. Simoncelli, “Range estimation by optical differentiation,” J. Opt. Soc. Am. A 15, 1777–1786 (1998).
    [CrossRef]

2003 (5)

Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing: high dynamic range in a wide field of view,” Int. J. Comput. Vision 53, 245–267 (2003).
[CrossRef]

F. M. Candocia, “Jointly registering images in domain and range by piecewise linear comparametric analysis,” IEEE Trans. Image Process. 12, 409–419 (2003).
[CrossRef]

M. D. Grossberg, S. K. Nayar, “Determining the camera response from images: what is knowable?,” IEEE Trans. Pattern Anal. Mach. Intell. 25, 1455–1467 (2003).
[CrossRef]

B. M. Ratliff, M. M. Hayat, J. S. Tyo, “Radiometrically accurate scene-based nonuniformity correction for array sensors,” J. Opt. Soc. Am. A 20, 1890–1899 (2003).
[CrossRef]

S. N. Torres, J. E. Pezoa, M. Hayat, “Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form,” Appl. Opt. 42, 5872–5881 (2003).
[CrossRef] [PubMed]

2002 (2)

S. Hsu, H. S. Sawhney, R. Kumar, “Automated mosaics via topology inference,” IEEE Comput. Graphics Appl. 22, 44–54 (2002).
[CrossRef]

N. Tabiryan, S. Nersisyan, “Liquid-crystal film eclipses the sun artificially,” Laser Focus World 38, 105–108 (2002).

2001 (2)

S. Peleg, M. Ben-Ezra, Y. Pritch, “Omnistereo: panoramic stereo imaging,” IEEE Trans. Pattern Anal. Mach. Intell. 23, 279–290 (2001).
[CrossRef]

H. Farid, “Blind inverse gamma correction,” IEEE Trans. Image Process. 10, 1428–1433 (2001).
[CrossRef]

2000 (4)

R. C. Hardie, M. M. Hayat, E. Armstrong, B. Yasuda, “Scene-based nonuniformity correction with video sequences and registration,” Appl. Opt. 39, 1241–1250 (2000).
[CrossRef]

S. Mann, “Comparametric equations with practical applications in quantigraphic image processing,” IEEE Trans. Image Process. 9, 1389–1406 (2000).
[CrossRef]

P. Thevenaz, M. Unser, “Optimization of mutual information for multiresolution image registration,” IEEE Trans. Image Process. 9, 2083–2099 (2000).
[CrossRef]

H. Y. Shum, R. Szeliski, “Systems and experiment paper: construction of panoramic image mosaics with global and local alignment,” Int. J. Comput. Vision 36, 101–130 (2000).
[CrossRef]

1999 (1)

1998 (2)

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

H. Farid, E. P. Simoncelli, “Range estimation by optical differentiation,” J. Opt. Soc. Am. A 15, 1777–1786 (1998).
[CrossRef]

1997 (1)

P. Viola, W. M. Wells, “Alignment by maximization of mutual information,” Int. J. Comput. Vision 24, 137–154 (1997).
[CrossRef]

1996 (1)

M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).

1995 (1)

E. M. Reynoso, G. M. Dubner, W. M. Goss, E. M. Arnal, “VLA observations of neutral hydrogen in the direction of Puppis A,” Astron. J. 110, 318–324 (1995).
[CrossRef]

1991 (1)

C. J. Lada, D. L. DePoy, K. M. Merrill, I. Gatley, “Infrared images of M17,” Astron. J. 374, 533–539 (1991).
[CrossRef]

1990 (2)

R. Kwok, J. C. Curlander, S. Pang, “An automated system for mosaicking spaceborne SAR imagery,” Int. J. Remote Sens. 11, 209–223 (1990).
[CrossRef]

J. M. Uson, S. P. Boughn, J. R. Kuhn, “The central galaxy in Abell 2029: an old supergiant,” Science 250, 539–540 (1990).
[CrossRef] [PubMed]

1983 (1)

P. J. Burt, E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graphics 2, 217–236 (1983).
[CrossRef]

1978 (1)

L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
[CrossRef]

Adelson, E. H.

P. J. Burt, E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graphics 2, 217–236 (1983).
[CrossRef]

Aggarwal, M.

M. Aggarwal, N. Ahuja, “High dynamic range panoramic imaging,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 2–9.

Ahuja, N.

M. Aggarwal, N. Ahuja, “High dynamic range panoramic imaging,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 2–9.

Amat, J.

R. Garcia, J. Batlle, X. Cufi, J. Amat, “Positioning an underwater vehicle through image mosaicking,” in Proceedings of IEEE International Conference on Robotics and Automation (IEEE Press, Piscataway, N.J., 2001), Part 3, pp. 2779–2784.

Anandan, P.

M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).

M. Hansen, P. Anandan, K. Dana, G. van der Wal, P. Burt, “Real-time scene stabilization and mosaic construction,” in Proceedings of IEEE Workshop on Applications of Computer Vision (IEEE Press, Piscataway, N.J., 1994), pp. 54–62.

Armstrong, E.

Arnal, E. M.

E. M. Reynoso, G. M. Dubner, W. M. Goss, E. M. Arnal, “VLA observations of neutral hydrogen in the direction of Puppis A,” Astron. J. 110, 318–324 (1995).
[CrossRef]

Awan, Z.

S. Negahdaripour, X. Xu, A. Khemene, Z. Awan, “3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROV’s/AUV’s and high-resolution sea-floor mapping,” in Proceedings of IEEE Workshop on Autonomous Underwater Vehicles (IEEE Press, Piscataway, N.J., 1998), pp. 191–200.

Banfield, D.

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

Batlle, J.

R. Garcia, J. Batlle, X. Cufi, J. Amat, “Positioning an underwater vehicle through image mosaicking,” in Proceedings of IEEE International Conference on Robotics and Automation (IEEE Press, Piscataway, N.J., 2001), Part 3, pp. 2779–2784.

Bell, M.

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

Belton, M. J. S.

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

Ben-Ezra, M.

S. Peleg, M. Ben-Ezra, Y. Pritch, “Omnistereo: panoramic stereo imaging,” IEEE Trans. Pattern Anal. Mach. Intell. 23, 279–290 (2001).
[CrossRef]

Bergen, J.

M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).

Boughn, S. P.

J. M. Uson, S. P. Boughn, J. R. Kuhn, “The central galaxy in Abell 2029: an old supergiant,” Science 250, 539–540 (1990).
[CrossRef] [PubMed]

Burt, P.

M. Hansen, P. Anandan, K. Dana, G. van der Wal, P. Burt, “Real-time scene stabilization and mosaic construction,” in Proceedings of IEEE Workshop on Applications of Computer Vision (IEEE Press, Piscataway, N.J., 1994), pp. 54–62.

Burt, P. J.

P. J. Burt, E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graphics 2, 217–236 (1983).
[CrossRef]

Candocia, F. M.

F. M. Candocia, “Jointly registering images in domain and range by piecewise linear comparametric analysis,” IEEE Trans. Image Process. 12, 409–419 (2003).
[CrossRef]

Capel, D.

D. Capel, A. Zisserman, “Automated mosaicing with super-resolution zoom,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1998), pp. 885–891.

Charette, M. P.

L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
[CrossRef]

Chen, P. H.

Cufi, X.

R. Garcia, J. Batlle, X. Cufi, J. Amat, “Positioning an underwater vehicle through image mosaicking,” in Proceedings of IEEE International Conference on Robotics and Automation (IEEE Press, Piscataway, N.J., 2001), Part 3, pp. 2779–2784.

Curlander, J. C.

R. Kwok, J. C. Curlander, S. Pang, “An automated system for mosaicking spaceborne SAR imagery,” Int. J. Remote Sens. 11, 209–223 (1990).
[CrossRef]

Dana, K.

M. Hansen, P. Anandan, K. Dana, G. van der Wal, P. Burt, “Real-time scene stabilization and mosaic construction,” in Proceedings of IEEE Workshop on Applications of Computer Vision (IEEE Press, Piscataway, N.J., 1994), pp. 54–62.

Debevec, P. E.

P. E. Debevec, J. Malik, “Recovering high dynamic range radiance maps from photographs,” in Proceedings of SIGGRAPH 97 (Association for Computing Machinery, New York, 1997), pp. 369–378.

DePoy, D. L.

C. J. Lada, D. L. DePoy, K. M. Merrill, I. Gatley, “Infrared images of M17,” Astron. J. 374, 533–539 (1991).
[CrossRef]

Dubner, G. M.

E. M. Reynoso, G. M. Dubner, W. M. Goss, E. M. Arnal, “VLA observations of neutral hydrogen in the direction of Puppis A,” Astron. J. 110, 318–324 (1995).
[CrossRef]

Duplaquet, M. L.

M. L. Duplaquet, “Building large image mosaics with invisible seam lines,” in Visual Information Processing VII, S. K. Park and R. D. Juday, eds., Proc. SPIE3387, 369–377 (1998).

Edwards, K.

L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
[CrossRef]

Eliason, E. M.

L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
[CrossRef]

Eustice, R.

R. Eustice, O. Pizarro, H. Singh, J. Howland, “UWIT: Underwater Image Toolbox for optical image processing and mosaicking in MATLAB,” in Proceedings of IEEE International Symposium on Underwater Technology (IEEE Press, Piscataway, N.J., 2002), pp. 141–145.

Farid, H.

H. Farid, “Blind inverse gamma correction,” IEEE Trans. Image Process. 10, 1428–1433 (2001).
[CrossRef]

H. Farid, E. P. Simoncelli, “Range estimation by optical differentiation,” J. Opt. Soc. Am. A 15, 1777–1786 (1998).
[CrossRef]

Garcia, R.

R. Garcia, J. Batlle, X. Cufi, J. Amat, “Positioning an underwater vehicle through image mosaicking,” in Proceedings of IEEE International Conference on Robotics and Automation (IEEE Press, Piscataway, N.J., 2001), Part 3, pp. 2779–2784.

Gatley, I.

C. J. Lada, D. L. DePoy, K. M. Merrill, I. Gatley, “Infrared images of M17,” Astron. J. 374, 533–539 (1991).
[CrossRef]

Gierasch, P. J.

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

Goss, W. M.

E. M. Reynoso, G. M. Dubner, W. M. Goss, E. M. Arnal, “VLA observations of neutral hydrogen in the direction of Puppis A,” Astron. J. 110, 318–324 (1995).
[CrossRef]

Grossberg, M. D.

M. D. Grossberg, S. K. Nayar, “Determining the camera response from images: what is knowable?,” IEEE Trans. Pattern Anal. Mach. Intell. 25, 1455–1467 (2003).
[CrossRef]

Gu, J.

S. Lin, J. Gu, S. Yamazaki, H. Shum, “Radiometric calibration from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. II, pp. 938–946.

Hansen, M.

M. Hansen, P. Anandan, K. Dana, G. van der Wal, P. Burt, “Real-time scene stabilization and mosaic construction,” in Proceedings of IEEE Workshop on Applications of Computer Vision (IEEE Press, Piscataway, N.J., 1994), pp. 54–62.

Hardie, R. C.

Hayat, M.

Hayat, M. M.

Howland, J.

R. Eustice, O. Pizarro, H. Singh, J. Howland, “UWIT: Underwater Image Toolbox for optical image processing and mosaicking in MATLAB,” in Proceedings of IEEE International Symposium on Underwater Technology (IEEE Press, Piscataway, N.J., 2002), pp. 141–145.

Hsu, S.

S. Hsu, H. S. Sawhney, R. Kumar, “Automated mosaics via topology inference,” IEEE Comput. Graphics Appl. 22, 44–54 (2002).
[CrossRef]

M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).

Ingersoll, A. P.

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

Inoue, S.

S. Inoue, Video Microscopy (Plenum, New York, 1986). pp. 209–214.

Irani, M.

M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).

Jia, J.

J. Jia, C. K. Tang, “Image registration with global and local luminance alignment,” in Proceedings of IEEE Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2003), Vol. I, pp. 156–163.

Kang, S. B.

S. B. Kang, R. Weiss, “Can we calibrate a camera using an image of a flat, textureless Lambertian surface?” in Proceedings of European Conference on Computer Vision, (Springer, New York, 2000), Part 2, pp. 640–653.

Khemene, A.

S. Negahdaripour, X. Xu, A. Khemene, Z. Awan, “3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROV’s/AUV’s and high-resolution sea-floor mapping,” in Proceedings of IEEE Workshop on Autonomous Underwater Vehicles (IEEE Press, Piscataway, N.J., 1998), pp. 191–200.

Khoo, I. C.

Kim, S. J.

S. J. Kim, M. Pollefeys, “Radiometric alignment of image sequences,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. I, pp. 645–652.

Kuhn, J. R.

J. M. Uson, S. P. Boughn, J. R. Kuhn, “The central galaxy in Abell 2029: an old supergiant,” Science 250, 539–540 (1990).
[CrossRef] [PubMed]

Kumar, R.

S. Hsu, H. S. Sawhney, R. Kumar, “Automated mosaics via topology inference,” IEEE Comput. Graphics Appl. 22, 44–54 (2002).
[CrossRef]

M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).

Kwok, R.

R. Kwok, J. C. Curlander, S. Pang, “An automated system for mosaicking spaceborne SAR imagery,” Int. J. Remote Sens. 11, 209–223 (1990).
[CrossRef]

Lada, C. J.

C. J. Lada, D. L. DePoy, K. M. Merrill, I. Gatley, “Infrared images of M17,” Astron. J. 374, 533–539 (1991).
[CrossRef]

Levin, A.

A. Levin, A. Zomet, S. Peleg, Y. Weiss, “Seamless image stitching in the gradient domain,” in Proceedings of European Conference in Computer Vision (Springer, New York, 2004), Part IV, pp. 377–390.

Lin, S.

S. Lin, J. Gu, S. Yamazaki, H. Shum, “Radiometric calibration from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. II, pp. 938–946.

Malik, J.

P. E. Debevec, J. Malik, “Recovering high dynamic range radiance maps from photographs,” in Proceedings of SIGGRAPH 97 (Association for Computing Machinery, New York, 1997), pp. 369–378.

Mann, R.

S. Mann, R. Mann, “Quantigraphic imaging: estimating the camera response and exposures from differently exposed images,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2001), Vol. 1, pp. 842–849.

Mann, S.

S. Mann, “Comparametric equations with practical applications in quantigraphic image processing,” IEEE Trans. Image Process. 9, 1389–1406 (2000).
[CrossRef]

S. Mann, R. Mann, “Quantigraphic imaging: estimating the camera response and exposures from differently exposed images,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2001), Vol. 1, pp. 842–849.

S. Mann, R. W. Picard, “On being ‘undigital’ with digital cameras: extending dynamic range by combining differently exposed pictures,” in Proceedings of IS&T 48th Annual Conference (Society for Imaging Science and Technology, Springfield, Va., 1995), pp. 422–428.

Merrill, K. M.

C. J. Lada, D. L. DePoy, K. M. Merrill, I. Gatley, “Infrared images of M17,” Astron. J. 374, 533–539 (1991).
[CrossRef]

Mitsunaga, T.

T. Mitsunaga, S. K. Nayar, “Radiometric self calibration,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1999), Vol. I, pp. 374–380.

Nayar, S. K.

Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing: high dynamic range in a wide field of view,” Int. J. Comput. Vision 53, 245–267 (2003).
[CrossRef]

M. D. Grossberg, S. K. Nayar, “Determining the camera response from images: what is knowable?,” IEEE Trans. Pattern Anal. Mach. Intell. 25, 1455–1467 (2003).
[CrossRef]

T. Mitsunaga, S. K. Nayar, “Radiometric self calibration,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1999), Vol. I, pp. 374–380.

Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 17–24.

Negahdaripour, S.

S. Negahdaripour, X. Xu, A. Khemene, Z. Awan, “3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROV’s/AUV’s and high-resolution sea-floor mapping,” in Proceedings of IEEE Workshop on Autonomous Underwater Vehicles (IEEE Press, Piscataway, N.J., 1998), pp. 191–200.

Nersisyan, S.

N. Tabiryan, S. Nersisyan, “Liquid-crystal film eclipses the sun artificially,” Laser Focus World 38, 105–108 (2002).

Pang, S.

R. Kwok, J. C. Curlander, S. Pang, “An automated system for mosaicking spaceborne SAR imagery,” Int. J. Remote Sens. 11, 209–223 (1990).
[CrossRef]

Pavel, M.

R. K. Sharma, M. Pavel, “Multisensor image registration,” in Proceedings of the Society for Information Display (Society for Information Display, Playa del Ray, Calif., 1997), Vol. XXVIII, pp. 951–954 (1997).

Peleg, S.

S. Peleg, M. Ben-Ezra, Y. Pritch, “Omnistereo: panoramic stereo imaging,” IEEE Trans. Pattern Anal. Mach. Intell. 23, 279–290 (2001).
[CrossRef]

A. Levin, A. Zomet, S. Peleg, Y. Weiss, “Seamless image stitching in the gradient domain,” in Proceedings of European Conference in Computer Vision (Springer, New York, 2004), Part IV, pp. 377–390.

Pezoa, J. E.

Picard, R. W.

S. Mann, R. W. Picard, “On being ‘undigital’ with digital cameras: extending dynamic range by combining differently exposed pictures,” in Proceedings of IS&T 48th Annual Conference (Society for Imaging Science and Technology, Springfield, Va., 1995), pp. 422–428.

Pizarro, O.

R. Eustice, O. Pizarro, H. Singh, J. Howland, “UWIT: Underwater Image Toolbox for optical image processing and mosaicking in MATLAB,” in Proceedings of IEEE International Symposium on Underwater Technology (IEEE Press, Piscataway, N.J., 2002), pp. 141–145.

Pollefeys, M.

S. J. Kim, M. Pollefeys, “Radiometric alignment of image sequences,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. I, pp. 645–652.

Pritch, Y.

S. Peleg, M. Ben-Ezra, Y. Pritch, “Omnistereo: panoramic stereo imaging,” IEEE Trans. Pattern Anal. Mach. Intell. 23, 279–290 (2001).
[CrossRef]

Ratliff, B. M.

Reynoso, E. M.

E. M. Reynoso, G. M. Dubner, W. M. Goss, E. M. Arnal, “VLA observations of neutral hydrogen in the direction of Puppis A,” Astron. J. 110, 318–324 (1995).
[CrossRef]

Sanchez, E. M.

L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
[CrossRef]

Sawhney, H. S.

S. Hsu, H. S. Sawhney, R. Kumar, “Automated mosaics via topology inference,” IEEE Comput. Graphics Appl. 22, 44–54 (2002).
[CrossRef]

Schechner, Y. Y.

Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing: high dynamic range in a wide field of view,” Int. J. Comput. Vision 53, 245–267 (2003).
[CrossRef]

Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 17–24.

Sharma, R. K.

R. K. Sharma, M. Pavel, “Multisensor image registration,” in Proceedings of the Society for Information Display (Society for Information Display, Playa del Ray, Calif., 1997), Vol. XXVIII, pp. 951–954 (1997).

Shih, M. Y.

Shum, H.

S. Lin, J. Gu, S. Yamazaki, H. Shum, “Radiometric calibration from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. II, pp. 938–946.

Shum, H. Y.

H. Y. Shum, R. Szeliski, “Systems and experiment paper: construction of panoramic image mosaics with global and local alignment,” Int. J. Comput. Vision 36, 101–130 (2000).
[CrossRef]

Simoncelli, E. P.

Singh, H.

R. Eustice, O. Pizarro, H. Singh, J. Howland, “UWIT: Underwater Image Toolbox for optical image processing and mosaicking in MATLAB,” in Proceedings of IEEE International Symposium on Underwater Technology (IEEE Press, Piscataway, N.J., 2002), pp. 141–145.

Soderblom, L. A.

L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
[CrossRef]

Szeliski, R.

H. Y. Shum, R. Szeliski, “Systems and experiment paper: construction of panoramic image mosaics with global and local alignment,” Int. J. Comput. Vision 36, 101–130 (2000).
[CrossRef]

Tabiryan, N.

N. Tabiryan, S. Nersisyan, “Liquid-crystal film eclipses the sun artificially,” Laser Focus World 38, 105–108 (2002).

Tang, C. K.

J. Jia, C. K. Tang, “Image registration with global and local luminance alignment,” in Proceedings of IEEE Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2003), Vol. I, pp. 156–163.

Thevenaz, P.

P. Thevenaz, M. Unser, “Optimization of mutual information for multiresolution image registration,” IEEE Trans. Image Process. 9, 2083–2099 (2000).
[CrossRef]

Törle, P.

P. Törle, “Scene-based correction of image sensor deficiencies,” MSc. thesis (Linköping Institute of Technology, Linköping, Sweden, 2003).

Torres, S. N.

Tyo, J. S.

Unser, M.

P. Thevenaz, M. Unser, “Optimization of mutual information for multiresolution image registration,” IEEE Trans. Image Process. 9, 2083–2099 (2000).
[CrossRef]

Uson, J. M.

J. M. Uson, S. P. Boughn, J. R. Kuhn, “The central galaxy in Abell 2029: an old supergiant,” Science 250, 539–540 (1990).
[CrossRef] [PubMed]

van der Wal, G.

M. Hansen, P. Anandan, K. Dana, G. van der Wal, P. Burt, “Real-time scene stabilization and mosaic construction,” in Proceedings of IEEE Workshop on Applications of Computer Vision (IEEE Press, Piscataway, N.J., 1994), pp. 54–62.

Vasavada, A. R.

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

Viola, P.

P. Viola, W. M. Wells, “Alignment by maximization of mutual information,” Int. J. Comput. Vision 24, 137–154 (1997).
[CrossRef]

Weiss, R.

S. B. Kang, R. Weiss, “Can we calibrate a camera using an image of a flat, textureless Lambertian surface?” in Proceedings of European Conference on Computer Vision, (Springer, New York, 2000), Part 2, pp. 640–653.

Weiss, Y.

A. Levin, A. Zomet, S. Peleg, Y. Weiss, “Seamless image stitching in the gradient domain,” in Proceedings of European Conference in Computer Vision (Springer, New York, 2004), Part IV, pp. 377–390.

Wells, W. M.

P. Viola, W. M. Wells, “Alignment by maximization of mutual information,” Int. J. Comput. Vision 24, 137–154 (1997).
[CrossRef]

Wood, M. V.

Xu, X.

S. Negahdaripour, X. Xu, A. Khemene, Z. Awan, “3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROV’s/AUV’s and high-resolution sea-floor mapping,” in Proceedings of IEEE Workshop on Autonomous Underwater Vehicles (IEEE Press, Piscataway, N.J., 1998), pp. 191–200.

Yamazaki, S.

S. Lin, J. Gu, S. Yamazaki, H. Shum, “Radiometric calibration from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. II, pp. 938–946.

Yasuda, B.

Zisserman, A.

D. Capel, A. Zisserman, “Automated mosaicing with super-resolution zoom,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1998), pp. 885–891.

Zomet, A.

A. Levin, A. Zomet, S. Peleg, Y. Weiss, “Seamless image stitching in the gradient domain,” in Proceedings of European Conference in Computer Vision (Springer, New York, 2004), Part IV, pp. 377–390.

ACM Trans. Graphics (1)

P. J. Burt, E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graphics 2, 217–236 (1983).
[CrossRef]

Appl. Opt. (2)

Astron. J. (2)

C. J. Lada, D. L. DePoy, K. M. Merrill, I. Gatley, “Infrared images of M17,” Astron. J. 374, 533–539 (1991).
[CrossRef]

E. M. Reynoso, G. M. Dubner, W. M. Goss, E. M. Arnal, “VLA observations of neutral hydrogen in the direction of Puppis A,” Astron. J. 110, 318–324 (1995).
[CrossRef]

Icarus (2)

L. A. Soderblom, K. Edwards, E. M. Eliason, E. M. Sanchez, M. P. Charette, “Global color variations on the Martian surface,” Icarus 34, 446–464 (1978).
[CrossRef]

A. R. Vasavada, A. P. Ingersoll, D. Banfield, M. Bell, P. J. Gierasch, M. J. S. Belton, “Galileo imaging of Jupiter’s atmosphere: the great red spot, equatorial region, and white ovals,” Icarus 135, 265–275 (1998).
[CrossRef]

IEEE Comput. Graphics Appl. (1)

S. Hsu, H. S. Sawhney, R. Kumar, “Automated mosaics via topology inference,” IEEE Comput. Graphics Appl. 22, 44–54 (2002).
[CrossRef]

IEEE Trans. Image Process. (4)

P. Thevenaz, M. Unser, “Optimization of mutual information for multiresolution image registration,” IEEE Trans. Image Process. 9, 2083–2099 (2000).
[CrossRef]

H. Farid, “Blind inverse gamma correction,” IEEE Trans. Image Process. 10, 1428–1433 (2001).
[CrossRef]

S. Mann, “Comparametric equations with practical applications in quantigraphic image processing,” IEEE Trans. Image Process. 9, 1389–1406 (2000).
[CrossRef]

F. M. Candocia, “Jointly registering images in domain and range by piecewise linear comparametric analysis,” IEEE Trans. Image Process. 12, 409–419 (2003).
[CrossRef]

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

M. D. Grossberg, S. K. Nayar, “Determining the camera response from images: what is knowable?,” IEEE Trans. Pattern Anal. Mach. Intell. 25, 1455–1467 (2003).
[CrossRef]

S. Peleg, M. Ben-Ezra, Y. Pritch, “Omnistereo: panoramic stereo imaging,” IEEE Trans. Pattern Anal. Mach. Intell. 23, 279–290 (2001).
[CrossRef]

Int. J. Comput. Vision (3)

H. Y. Shum, R. Szeliski, “Systems and experiment paper: construction of panoramic image mosaics with global and local alignment,” Int. J. Comput. Vision 36, 101–130 (2000).
[CrossRef]

Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing: high dynamic range in a wide field of view,” Int. J. Comput. Vision 53, 245–267 (2003).
[CrossRef]

P. Viola, W. M. Wells, “Alignment by maximization of mutual information,” Int. J. Comput. Vision 24, 137–154 (1997).
[CrossRef]

Int. J. Remote Sens. (1)

R. Kwok, J. C. Curlander, S. Pang, “An automated system for mosaicking spaceborne SAR imagery,” Int. J. Remote Sens. 11, 209–223 (1990).
[CrossRef]

J. Opt. Soc. Am. A (2)

Laser Focus World (1)

N. Tabiryan, S. Nersisyan, “Liquid-crystal film eclipses the sun artificially,” Laser Focus World 38, 105–108 (2002).

Opt. Express (1)

Science (1)

J. M. Uson, S. P. Boughn, J. R. Kuhn, “The central galaxy in Abell 2029: an old supergiant,” Science 250, 539–540 (1990).
[CrossRef] [PubMed]

Signal Process. (1)

M. Irani, P. Anandan, J. Bergen, R. Kumar, S. Hsu, “Efficient representations of video sequences and their application,” Signal Process. 8, 327–351 (1996).

Other (24)

R. K. Sharma, M. Pavel, “Multisensor image registration,” in Proceedings of the Society for Information Display (Society for Information Display, Playa del Ray, Calif., 1997), Vol. XXVIII, pp. 951–954 (1997).

We may avoid the apperance of trivial solution by expressing Eq. (15) in a matrix formulation. This is only one of the possible realizations of the requirement to avoid a nontrivial g. Another possibility is to fix the boundary range values of g.

We placed the filter a few centimeters ahead of the lens. If the filter is placed right next to the lens, it affects the aperture properties[48] without producing spatially varying effects in the image.

S. Negahdaripour, X. Xu, A. Khemene, Z. Awan, “3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROV’s/AUV’s and high-resolution sea-floor mapping,” in Proceedings of IEEE Workshop on Autonomous Underwater Vehicles (IEEE Press, Piscataway, N.J., 1998), pp. 191–200.

M. Hansen, P. Anandan, K. Dana, G. van der Wal, P. Burt, “Real-time scene stabilization and mosaic construction,” in Proceedings of IEEE Workshop on Applications of Computer Vision (IEEE Press, Piscataway, N.J., 1994), pp. 54–62.

M. Aggarwal, N. Ahuja, “High dynamic range panoramic imaging,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 2–9.

Y. Y. Schechner, S. K. Nayar, “Generalized mosaicing,” in Proceedings of IEEE International Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2001), Vol. I, pp. 17–24.

A. Levin, A. Zomet, S. Peleg, Y. Weiss, “Seamless image stitching in the gradient domain,” in Proceedings of European Conference in Computer Vision (Springer, New York, 2004), Part IV, pp. 377–390.

S. B. Kang, R. Weiss, “Can we calibrate a camera using an image of a flat, textureless Lambertian surface?” in Proceedings of European Conference on Computer Vision, (Springer, New York, 2000), Part 2, pp. 640–653.

In different communities the terms mosaicing[5, 6] and mosaicking[7, 8, 9, 10] are used.

D. Capel, A. Zisserman, “Automated mosaicing with super-resolution zoom,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1998), pp. 885–891.

R. Eustice, O. Pizarro, H. Singh, J. Howland, “UWIT: Underwater Image Toolbox for optical image processing and mosaicking in MATLAB,” in Proceedings of IEEE International Symposium on Underwater Technology (IEEE Press, Piscataway, N.J., 2002), pp. 141–145.

R. Garcia, J. Batlle, X. Cufi, J. Amat, “Positioning an underwater vehicle through image mosaicking,” in Proceedings of IEEE International Conference on Robotics and Automation (IEEE Press, Piscataway, N.J., 2001), Part 3, pp. 2779–2784.

M. L. Duplaquet, “Building large image mosaics with invisible seam lines,” in Visual Information Processing VII, S. K. Park and R. D. Juday, eds., Proc. SPIE3387, 369–377 (1998).

P. Törle, “Scene-based correction of image sensor deficiencies,” MSc. thesis (Linköping Institute of Technology, Linköping, Sweden, 2003).

S. Lin, J. Gu, S. Yamazaki, H. Shum, “Radiometric calibration from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. II, pp. 938–946.

S. Inoue, Video Microscopy (Plenum, New York, 1986). pp. 209–214.

The radiometric response function is usually monotonically increasing. It monotonically decreases in negative films and in some camera modes.

P. E. Debevec, J. Malik, “Recovering high dynamic range radiance maps from photographs,” in Proceedings of SIGGRAPH 97 (Association for Computing Machinery, New York, 1997), pp. 369–378.

S. Mann, R. W. Picard, “On being ‘undigital’ with digital cameras: extending dynamic range by combining differently exposed pictures,” in Proceedings of IS&T 48th Annual Conference (Society for Imaging Science and Technology, Springfield, Va., 1995), pp. 422–428.

S. Mann, R. Mann, “Quantigraphic imaging: estimating the camera response and exposures from differently exposed images,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2001), Vol. 1, pp. 842–849.

T. Mitsunaga, S. K. Nayar, “Radiometric self calibration,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 1999), Vol. I, pp. 374–380.

S. J. Kim, M. Pollefeys, “Radiometric alignment of image sequences,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE Press, Piscataway, N.J., 2004), Vol. I, pp. 645–652.

J. Jia, C. K. Tang, “Image registration with global and local luminance alignment,” in Proceedings of IEEE Conference on Computer Vision (IEEE Press, Piscataway, N.J., 2003), Vol. I, pp. 156–163.

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Figures (12)

Fig. 1
Fig. 1

Illustrating human sensitivity to radiometric mismatch. Several consecutive image parts were biased by 4% with respect to each other, as if stitched by a process of mosaicking. Even such a small mismatch creates clear visual artifacts.

Fig. 2
Fig. 2

Several frames from a simulated image sequence acquired by a camera with optical nonuniformity. Owing to the nonuniformity, each scene point is acquired with a different optical setting. The selected region is saturated in frame 5 and not saturated in frames 1 and 3.

Fig. 3
Fig. 3

Imaging system model. The optical system induces spatial inhomogeneities on the image, which are characterized by M ( x ) . The camera electronics has an unknown radiometric response r ( I ) .

Fig. 4
Fig. 4

Images created with the filter M ( x ) and the radiometric response function r ( I ) . Scene features become darker toward the frame periphery.

Fig. 5
Fig. 5

Solid curve, the true inverted radiometric response function r 1 ( v ) and the true nonuniformity function M ( x ) . Both functions are concatenated. Dashed curve, the estimated solution r ̂ 1 ( v ) and M ̂ ( x ) (concatenated).

Fig. 6
Fig. 6

Image mosaic constructed in the simulation. No seams appear in the mosaic, although the original images suffered from an unknown vignetting, and the recovered vignetting and radiometric response erred by an exponential function. No dedicated seam-removal method was applied.

Fig. 7
Fig. 7

Image mosaic constructed by direct stitching without compensating for the radiometric response function r ( I ) and the optical nonuniformity M ( x ) .

Fig. 8
Fig. 8

Experiment that uses real data. Solid curve, the true inverted radiometric response function r 1 ( v ) and the true nonuniform function M ( x ) . Both functions are concatenated. Dashed curve, the estimated solution r ̂ 1 ( v ) and M ̂ ( x ) (concatenated).

Fig. 9
Fig. 9

Image frames sampled from a sequence acquired by a Nikon D100 digital camera. A spatially varying optical filter had been attached to the camera lens. Scene features become darker toward the periphery of each frame.

Fig. 10
Fig. 10

Image mosaics constructed on the basis of real experimental data. Two different values of K were used to construct these mosaics. Seams are hardly apparent, although the original images suffered from an unknown vignetting, and the recovered vignetting and radiometric response erred by an exponential function. No dedicated seam-removal method was applied.

Fig. 11
Fig. 11

Image mosaic constructed by direct stitching without compensating for the radiometric response function r ( I ) and for the optical nonuniformity M ( x ) .

Fig. 12
Fig. 12

Arbitrary 2D matrix B.

Equations (42)

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

v ( x ) = r [ I ̃ ( x ) ] = r [ M ( x ) I ( x ) ] .
r 1 [ v ( x ) ] = I ̃ ( x ) = M ( x ) I ( x ) .
log { r 1 [ v ( x ) ] } = log [ M ( x ) ] + log [ I ( x ) ] .
g [ v ( x p f 0 ) ] = l ( x p f 0 ) + log ( I ) ,
g [ v ( x p f 1 ) ] = l ( x p f 1 ) + log ( I ) .
Q [ v ( x p f 0 ) , v ( x p f 1 ) , x p f 0 , x p f 1 ] g [ v ( x p f 0 ) ] g [ v ( x p f 1 ) ] l ( x p f 0 ) + l ( x p f 1 ) .
Q [ v ( x p f 0 ) , v ( x p f 1 ) , x p f 0 , x p f 1 ] = 0 .
Ψ 0 = p = 1 P f = 1 F 1 e = f + 1 F Q 2 [ v ( x p f ) , v ( x p e ) , x p f , x p e ] + λ g v = 0 v max g ( v ) 2 + λ l x = 1 N y = 1 N [ 2 l ( x ) ] 2 .
g ( v ) g ( v 1 ) 2 g ( v ) + g ( v + 1 ) ,
2 l ( x ) l ( x 1 , y ) + l ( x , y 1 ) 4 l ( x , y ) + l ( x + 1 , y ) + l ( x , y + 1 ) .
Ψ 1 = p = 1 P f = 1 F 1 e = f + 1 F w 2 [ v ( x p f ) , v ( x p e ) ] Q 2 [ v ( x p f ) , v ( x p e ) , x p f , x p e ] + λ g v = 0 v max g ( v ) 2 + λ l x = 1 N y = 1 N [ 2 l ( x ) ] 2 .
w ( v 1 , v 2 ) = v 1 v 2 ( v 1 2 + v 2 2 ) 1 2 .
r 1 v = r 1 ( v + 1 ) r 1 ( v ) = k ,
r 1 ( v ) = ( v v start ) k + I start ,
Ψ = Ψ 1 + λ m v = v start v end { g ( v ) log [ ( v v start ) k + I start ] } 2 .
Rs = 0 ,
s = ( g l )
g = [ g ( 0 ) , g ( v max ) ] T , l = [ l ( 1 ) , l ( N ̃ ) ] T .
R [ n , v ( x p f 0 ) ] = R [ n , v ( x p f 1 ) ] = 1 ,
R ( n , x ̃ p f 0 ) = R ( n , x ̃ p f 1 ) = 1 ,
W ( n , n ) = w [ v ( x p f 0 ) , v ( x p f 1 ) ] ,
D ̃ = [ 1 2 1 0 0 1 2 1 0 0 0 1 2 1 ] .
D g = [ D ̃ v max 0 N ̃ ] ,
D l = [ 0 v max L ̃ ] ,
s ̂ = arg min s ( s t A t As ) ,
A = [ WR λ g D g λ l D l ] .
D l = [ 0 v max D ̃ N ̃ ] ,
r ̂ 1 ( v ) = exp [ g ̂ ( v ) ] = exp [ Kg ( v ) ] = [ r 1 ( v ) ] K ,
M ̂ ( x ) = exp [ l ̂ ( x ) ] = exp [ Kl ( x ) ] = [ M ( x ) ] K .
I ̂ = [ r 1 ( v ) ] K [ M ( x ) ] K = I K .
I f = r ̂ 1 [ v ( x ) ] M ̂ ( x ) ,
Δ I f = I f v ( x ) Δ v ( x ) .
I ̂ = Δ I ̂ 2 f I f Δ I f 2 ,
Δ I ̂ = ( f 1 Δ I f 2 ) 1 2 .
g ( v f 1 ) g ( v f 2 ) l ( x f 1 ) + l ( x f 2 ) = 0 ± Δ Q ( v f 1 , v f 2 ) ,
Δ Q ( v f 1 , v f 2 ) = σ [ ( Q v f 1 ) 2 + ( Q v f 2 ) 2 ] 1 2 .
Δ Q ( v f 1 , v f 2 ) = σ { [ 1 r 1 ( v f 1 ) r 1 v f 1 ] 2 + [ 1 r 1 ( v f 2 ) r 1 v f 2 ] 2 } 1 2 .
Δ Q ( v f 1 , v f 2 ) = γ σ [ ( 1 v f 1 ) 2 + ( 1 v f 2 ) 2 ] 1 2 = γ σ { v f 1 v f 2 [ ( v f 1 ) 2 + ( v f 2 ) 2 ] 1 2 } 1 .
w ( v f 1 , v f 2 ) = v f 1 v f 2 [ ( v f 1 ) 2 + ( v f 2 ) 2 ] 1 2 .
L ̃ ( n , n ) = { 4 if N < n < N 2 N and n j N , j N + 1 , j [ 1 , N 1 ] 0 if n = 1 , N , N 2 N + 1 , N 2 2 otherwise } ,
L ̃ ( n , n ± 1 ) = { 1 if n j N , j N + 1 , j [ 0 , N ] 0 otherwise } ,
L ̃ ( n , n ± N ) = { 1 if N < n N 2 N 0 otherwise } .

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