Abstract

Image recovery under noise is widely studied. However, there is little emphasis on performance as a function of object size. In this work we analyze the probability of recovery as a function of object spatial frequency. The analysis uses a physical model for the acquired signal and noise, and also accounts for potential postacquisition noise filtering. Linear-systems analysis yields an effective cutoff frequency, which is induced by noise, despite having no optical blur in the imaging model. This means that a low signal-to-noise ratio (SNR) in images causes resolution loss, similar to image blur. We further consider the effect on SNR of pointwise image formation models, such as added specular or indirect reflections, additive scattering, radiance attenuation in haze, and flash photography. The result is a tool that assesses the ability to recover (within a desirable success rate) an object or feature having a certain size, distance from the camera, and radiance difference from its nearby background, per attenuation coefficient of the medium. The bounds rely on the camera specifications.

© 2012 Optical Society of America

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2011

R. Mantiuk, K. Kim, A. Rempel, and W. Heidrich, “Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions,” ACM Trans. Graph. 30, 40 (2011).
[CrossRef]

2010

P. Chatterjee and P. Milanfar, “Is denoising dead?,” IEEE Trans. Image Process. 19, 895–911 (2010).
[CrossRef]

2009

P. Chatterjee and P. Milanfar, “Clustering-based denoising with locally learned dictionaries,” IEEE Trans. Image Process. 18, 1438–1451 (2009).
[CrossRef]

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Machine Intell. 31, 385–399 (2009).
[CrossRef]

H. Barrett, “NEQ: its progenitors and progeny,” Proc. SPIE 7263, 72630F (2009).

2008

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic estimation and removal of noise from a single image,” IEEE Trans. Pattern Anal. Machine Intell. 30, 299–314 (2008).
[CrossRef]

R. Fattal, “Single image dehazing,” ACM Trans. Graph. 27, 72, (2008).
[CrossRef]

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

2007

Y. Y. Schechner, S. K. Nayar, and P. N. Belhumeur, “Multiplexing for optimal lighting,” IEEE Trans. Pattern Anal. Machine Intell. 29, 1339–1354 (2007).
[CrossRef]

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3-d transform-domain collaborative filtering,” IEEE Trans. Image Process. 16, 2080–2095 (2007).
[CrossRef]

S. Bobrov, and Y. Y. Schechner, “Image-based prediction of imaging and vision performance,” J. Opt. Soc. Am. A 24, 1920–1929 (2007).
[CrossRef]

2006

M. Elad and M. Aharon, “Image denoising via sparse and redundant representations over learned dictionaries,” IEEE Trans. Image Process. 15, 3736–3745 (2006).
[CrossRef]

S. K. Nayar, G. Krishnan, M. D. Grossberg, and R. Raskar, “Fast separation of direct and global components of a scene using high frequency illumination,” ACM Trans. Graph. 25, 935–944 (2006).
[CrossRef]

M. Shahram and P. Milanfar, “Statistical and information-theoretic analysis of resolution in imaging,” IEEE Trans. Inf. Theory 52, 3411–3437 (2006).
[CrossRef]

2005

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

A. Buades, B. Coll, and J. M. Morel, “A review of image denoising algorithms, with a new one,” Multiscale Model. Simul. 4, 490–530 (2005).
[CrossRef]

A. Agrawal, R. Raskar, S. K. Nayar, and Y. Li, “Removing photography artifacts using gradient projection and flash-exposure sampling,” ACM Trans. Graph. 24, 828–835 (2005).
[CrossRef]

B. Wells, “MTF provides an image-quality metric,” Laser Focus World 41 (2005).

2004

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

M. Shahram and P. Milanfar, “Imaging below the diffraction limit: a statistical analysis,” IEEE Trans. Image Process. 13, 677–689 (2004).
[CrossRef]

Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[CrossRef]

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

2003

J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Image denoising using scale mixtures of gaussians in the wavelet domain,” IEEE Trans. Image Process. 12, 1338–1351 (2003).
[CrossRef]

Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar, “Polarization-based vision through haze,” Appl. Opt. 42, 511–525 (2003).
[CrossRef]

2001

K. Tan, and J. P. Oakley, “Physics-based approach to color image enhancement in poor visibility conditions,” J. Opt. Soc. Am. A 18, 2460–2467 (2001).
[CrossRef]

R. D. Fiete, and T. A. Tantalo, “Comparison of SNR image quality metrics for remote sensing systems,” Opt. Eng. 40, 574–585 (2001).
[CrossRef]

2000

1999

1997

S. K. Nayar, X. S. Fang, and T. Boult, “Separation of reflection components using color and polarization,” Int. J. Comput. Vis. 21, 163–186 (1997).
[CrossRef]

J. C. Leachtenauer, W. Malila, J. Irvine, L. Colburn, and N. Salvaggio, “General image-quality equation: GIQE,” Appl. Opt. 36, 8322–8328 (1997).
[CrossRef]

1994

G. E. Healey and R. Kondepudy, “Radiometric CCD camera calibration and noise estimation,” IEEE Trans. Pattern Anal. Machine Intell. 16, 267–276 (1994).
[CrossRef]

1990

1987

M. Unser, B. L. Trus, and A. C. Steven, “A new resolution criterion based on spectral signal-to-noise ratios,” Ultramicroscopy 23, 39–51 (1987).
[CrossRef]

1972

D. H. Kelly, “Adaptation effects on spatio-temporal sine-wave thresholds,” Vis. Res. 12, 89–101 (1972).
[CrossRef]

1968

1964

O. Schade, “An evaluation of photographic image quality and resolving power,” J. Soc. Motion Pict. Telev. Eng. 73, 81–119 (1964).

Abbott, L. F.

P. Dayan and L. F. Abbott, Theoretical Neuroscience (MIT, 2001), Chap. 4, pp. 139–141.

Adelson, E. H.

Agrawal, A.

A. Agrawal, R. Raskar, S. K. Nayar, and Y. Li, “Removing photography artifacts using gradient projection and flash-exposure sampling,” ACM Trans. Graph. 24, 828–835 (2005).
[CrossRef]

Agrawala, M.

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

Aharon, M.

M. Elad and M. Aharon, “Image denoising via sparse and redundant representations over learned dictionaries,” IEEE Trans. Image Process. 15, 3736–3745 (2006).
[CrossRef]

Barrett, H.

Belhumeur, P.

J. Gu, R. Ramamoorthi, P. Belhumeur, and S. K. Nayar, “Dirty glass: rendering contamination on transparent surfaces,” in Eurographics Symposium on Rendering (Springer, 2007), p. 159–170.

Belhumeur, P. N.

Y. Y. Schechner, S. K. Nayar, and P. N. Belhumeur, “Multiplexing for optimal lighting,” IEEE Trans. Pattern Anal. Machine Intell. 29, 1339–1354 (2007).
[CrossRef]

Bobrov, S.

Bolas, M.

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

Boult, T.

S. K. Nayar, X. S. Fang, and T. Boult, “Separation of reflection components using color and polarization,” Int. J. Comput. Vis. 21, 163–186 (1997).
[CrossRef]

Bovik, A.

Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[CrossRef]

Buades, A.

A. Buades, B. Coll, and J. M. Morel, “A review of image denoising algorithms, with a new one,” Multiscale Model. Simul. 4, 490–530 (2005).
[CrossRef]

Burgess, A.

Chatterjee, P.

P. Chatterjee and P. Milanfar, “Is denoising dead?,” IEEE Trans. Image Process. 19, 895–911 (2010).
[CrossRef]

P. Chatterjee and P. Milanfar, “Clustering-based denoising with locally learned dictionaries,” IEEE Trans. Image Process. 18, 1438–1451 (2009).
[CrossRef]

Chen, B.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

Chitwood, D.

Cohen, M.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

Cohen-Or, D.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

Colburn, L.

Coll, B.

A. Buades, B. Coll, and J. M. Morel, “A review of image denoising algorithms, with a new one,” Multiscale Model. Simul. 4, 490–530 (2005).
[CrossRef]

Cunningham, I.

Dabov, K.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3-d transform-domain collaborative filtering,” IEEE Trans. Image Process. 16, 2080–2095 (2007).
[CrossRef]

Davidson, M. W.

T. J. Fellers, and M. W. Davidson, “CCD noise sources and signal-to-noise ratio,” Optical Microscopy Primer (Molecular Expressions™) (2004).

Dayan, P.

P. Dayan and L. F. Abbott, Theoretical Neuroscience (MIT, 2001), Chap. 4, pp. 139–141.

Debevec, P.

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

Deussen, O.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

Diner, D.

Y. Schechner, D. Diner, and J. Martonchik, “Spaceborne underwater imaging,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2011), p. 1–8.

Durand, F.

S. Hasinoff, F. Durand, and W. Freeman, “Noise-optimal capture for high dynamic range photography,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2010), p. 553–560.

Egiazarian, K.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3-d transform-domain collaborative filtering,” IEEE Trans. Image Process. 16, 2080–2095 (2007).
[CrossRef]

Elad, M.

M. Elad and M. Aharon, “Image denoising via sparse and redundant representations over learned dictionaries,” IEEE Trans. Image Process. 15, 3736–3745 (2006).
[CrossRef]

Fang, X. S.

S. K. Nayar, X. S. Fang, and T. Boult, “Separation of reflection components using color and polarization,” Int. J. Comput. Vis. 21, 163–186 (1997).
[CrossRef]

Farid, H.

Fattal, R.

R. Fattal, “Single image dehazing,” ACM Trans. Graph. 27, 72, (2008).
[CrossRef]

Fellers, T. J.

T. J. Fellers, and M. W. Davidson, “CCD noise sources and signal-to-noise ratio,” Optical Microscopy Primer (Molecular Expressions™) (2004).

Fiete, R. D.

R. D. Fiete, and T. A. Tantalo, “Comparison of SNR image quality metrics for remote sensing systems,” Opt. Eng. 40, 574–585 (2001).
[CrossRef]

Foi, A.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3-d transform-domain collaborative filtering,” IEEE Trans. Image Process. 16, 2080–2095 (2007).
[CrossRef]

Freeman, W.

S. Hasinoff, F. Durand, and W. Freeman, “Noise-optimal capture for high dynamic range photography,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2010), p. 553–560.

Freeman, W. T.

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic estimation and removal of noise from a single image,” IEEE Trans. Pattern Anal. Machine Intell. 30, 299–314 (2008).
[CrossRef]

Gardner, A.

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

Geisler, W.

W. Geisler, Ideal Observer Analysis (MIT Press, 2003), pp. 825–837.

Grossberg, M. D.

S. K. Nayar, G. Krishnan, M. D. Grossberg, and R. Raskar, “Fast separation of direct and global components of a scene using high frequency illumination,” ACM Trans. Graph. 25, 935–944 (2006).
[CrossRef]

Gu, J.

J. Gu, R. Ramamoorthi, P. Belhumeur, and S. K. Nayar, “Dirty glass: rendering contamination on transparent surfaces,” in Eurographics Symposium on Rendering (Springer, 2007), p. 159–170.

Hasinoff, S.

S. Hasinoff, F. Durand, and W. Freeman, “Noise-optimal capture for high dynamic range photography,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2010), p. 553–560.

Hawkins, T.

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

Healey, G. E.

G. E. Healey and R. Kondepudy, “Radiometric CCD camera calibration and noise estimation,” IEEE Trans. Pattern Anal. Machine Intell. 16, 267–276 (1994).
[CrossRef]

Heidrich, W.

R. Mantiuk, K. Kim, A. Rempel, and W. Heidrich, “Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions,” ACM Trans. Graph. 30, 40 (2011).
[CrossRef]

Henry, R. C.

Hoppe, H.

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

Horowitz, M.

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

Ikeuchi, K.

J. Takamatsu, Y. Matsushita, and K. Ikeuchi, “Estimating radiometric response functions from image noise variance,” in Proceedings of European Conference on Computer Vision (Springer, 2008), pp. 623–637.

Inoué, S.

S. Inoué, and K. R. Spring, Video Microscopy: The Fundamentals, 2nd ed (Springer, 1997), Chap. 7, p. 316.

Irvine, J.

Kaftory, R.

R. Kaftory, Y. Y. Schechner, and Y. Y. Zeevi, “Variational distance-dependent image restoration,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), pp. 1–8.

Kang, S. B.

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic estimation and removal of noise from a single image,” IEEE Trans. Pattern Anal. Machine Intell. 30, 299–314 (2008).
[CrossRef]

Katkovnik, V.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3-d transform-domain collaborative filtering,” IEEE Trans. Image Process. 16, 2080–2095 (2007).
[CrossRef]

Keelan, B. W.

B. W. Keelan, Handbook of Image Quality (Dekker, 2002),Chaps. 2, 3.

Kelly, D. H.

D. H. Kelly, “Adaptation effects on spatio-temporal sine-wave thresholds,” Vis. Res. 12, 89–101 (1972).
[CrossRef]

Kim, K.

R. Mantiuk, K. Kim, A. Rempel, and W. Heidrich, “Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions,” ACM Trans. Graph. 30, 40 (2011).
[CrossRef]

Kinzly, R.

Kondepudy, R.

G. E. Healey and R. Kondepudy, “Radiometric CCD camera calibration and noise estimation,” IEEE Trans. Pattern Anal. Machine Intell. 16, 267–276 (1994).
[CrossRef]

Kopeika, N. S.

N. S. Kopeika, A System Engineering Approach to Imaging (SPIE, 1998), Chaps. 9, 10, 19.

Kopf, J.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

Koreban, F.

F. Koreban, and Y. Y. Schechner, “Geometry by deflaring,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2009), p. 1–8.

Krishnan, G.

S. K. Nayar, G. Krishnan, M. D. Grossberg, and R. Raskar, “Fast separation of direct and global components of a scene using high frequency illumination,” ACM Trans. Graph. 25, 935–944 (2006).
[CrossRef]

Kutulakos, K. N.

S. M. Seitz, Y. Matsushita, and K. N. Kutulakos, “A theory of inverse light transport,” in Proceedings of IEEE International Conference on Computer Vision (IEEE, 2005), pp. 1440–1447.

Leachtenauer, J. C.

Levin, A.

A. Levin and B. Nadler, “Natural image denoising: optimality and inherent bounds,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2010), p. 2833–2840.

Levoy, M.

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

Li, Y.

A. Agrawal, R. Raskar, S. K. Nayar, and Y. Li, “Removing photography artifacts using gradient projection and flash-exposure sampling,” ACM Trans. Graph. 24, 828–835 (2005).
[CrossRef]

Lin, S.

Y. Matsushita, and S. Lin, “Radiometric calibration from noise distributions,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), p. 1–8.

Lischinski, D.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

Liu, C.

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic estimation and removal of noise from a single image,” IEEE Trans. Pattern Anal. Machine Intell. 30, 299–314 (2008).
[CrossRef]

Lloyd, J.

J. Lloyd, Thermal Imaging Systems (Springer, 1975). Chaps. 5, 10.

Mahadev, S.

Malila, W.

Mantiuk, R.

R. Mantiuk, K. Kim, A. Rempel, and W. Heidrich, “Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions,” ACM Trans. Graph. 30, 40 (2011).
[CrossRef]

Martonchik, J.

Y. Schechner, D. Diner, and J. Martonchik, “Spaceborne underwater imaging,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2011), p. 1–8.

Matsushita, Y.

Y. Matsushita, and S. Lin, “Radiometric calibration from noise distributions,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), p. 1–8.

J. Takamatsu, Y. Matsushita, and K. Ikeuchi, “Estimating radiometric response functions from image noise variance,” in Proceedings of European Conference on Computer Vision (Springer, 2008), pp. 623–637.

S. M. Seitz, Y. Matsushita, and K. N. Kutulakos, “A theory of inverse light transport,” in Proceedings of IEEE International Conference on Computer Vision (IEEE, 2005), pp. 1440–1447.

McDowall, I.

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

Milanfar, P.

P. Chatterjee and P. Milanfar, “Is denoising dead?,” IEEE Trans. Image Process. 19, 895–911 (2010).
[CrossRef]

P. Chatterjee and P. Milanfar, “Clustering-based denoising with locally learned dictionaries,” IEEE Trans. Image Process. 18, 1438–1451 (2009).
[CrossRef]

M. Shahram and P. Milanfar, “Statistical and information-theoretic analysis of resolution in imaging,” IEEE Trans. Inf. Theory 52, 3411–3437 (2006).
[CrossRef]

M. Shahram and P. Milanfar, “Imaging below the diffraction limit: a statistical analysis,” IEEE Trans. Image Process. 13, 677–689 (2004).
[CrossRef]

Morel, J. M.

A. Buades, B. Coll, and J. M. Morel, “A review of image denoising algorithms, with a new one,” Multiscale Model. Simul. 4, 490–530 (2005).
[CrossRef]

Nadler, B.

A. Levin and B. Nadler, “Natural image denoising: optimality and inherent bounds,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2010), p. 2833–2840.

Narasimhan, S. G.

Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar, “Polarization-based vision through haze,” Appl. Opt. 42, 511–525 (2003).
[CrossRef]

S. G. Narasimhan, C. Wang, and S. K. Nayar, “All the images of an outdoor scene,” in Proceedings of European Conference on Computer Vision (IEEE, 2002), pp. 148–162.

Nayar, S. K.

Y. Y. Schechner, S. K. Nayar, and P. N. Belhumeur, “Multiplexing for optimal lighting,” IEEE Trans. Pattern Anal. Machine Intell. 29, 1339–1354 (2007).
[CrossRef]

S. K. Nayar, G. Krishnan, M. D. Grossberg, and R. Raskar, “Fast separation of direct and global components of a scene using high frequency illumination,” ACM Trans. Graph. 25, 935–944 (2006).
[CrossRef]

A. Agrawal, R. Raskar, S. K. Nayar, and Y. Li, “Removing photography artifacts using gradient projection and flash-exposure sampling,” ACM Trans. Graph. 24, 828–835 (2005).
[CrossRef]

Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar, “Polarization-based vision through haze,” Appl. Opt. 42, 511–525 (2003).
[CrossRef]

S. K. Nayar, X. S. Fang, and T. Boult, “Separation of reflection components using color and polarization,” Int. J. Comput. Vis. 21, 163–186 (1997).
[CrossRef]

S. G. Narasimhan, C. Wang, and S. K. Nayar, “All the images of an outdoor scene,” in Proceedings of European Conference on Computer Vision (IEEE, 2002), pp. 148–162.

J. Gu, R. Ramamoorthi, P. Belhumeur, and S. K. Nayar, “Dirty glass: rendering contamination on transparent surfaces,” in Eurographics Symposium on Rendering (Springer, 2007), p. 159–170.

Neubert, B.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

Oakley, J. P.

Petschnigg, G.

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

Portilla, J.

J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Image denoising using scale mixtures of gaussians in the wavelet domain,” IEEE Trans. Image Process. 12, 1338–1351 (2003).
[CrossRef]

Ramamoorthi, R.

J. Gu, R. Ramamoorthi, P. Belhumeur, and S. K. Nayar, “Dirty glass: rendering contamination on transparent surfaces,” in Eurographics Symposium on Rendering (Springer, 2007), p. 159–170.

Raskar, R.

S. K. Nayar, G. Krishnan, M. D. Grossberg, and R. Raskar, “Fast separation of direct and global components of a scene using high frequency illumination,” ACM Trans. Graph. 25, 935–944 (2006).
[CrossRef]

A. Agrawal, R. Raskar, S. K. Nayar, and Y. Li, “Removing photography artifacts using gradient projection and flash-exposure sampling,” ACM Trans. Graph. 24, 828–835 (2005).
[CrossRef]

Rempel, A.

R. Mantiuk, K. Kim, A. Rempel, and W. Heidrich, “Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions,” ACM Trans. Graph. 30, 40 (2011).
[CrossRef]

Roetling, P.

Salvaggio, N.

Schade, O.

O. Schade, “An evaluation of photographic image quality and resolving power,” J. Soc. Motion Pict. Telev. Eng. 73, 81–119 (1964).

Schechner, Y.

Y. Schechner, D. Diner, and J. Martonchik, “Spaceborne underwater imaging,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2011), p. 1–8.

Schechner, Y. Y.

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Machine Intell. 31, 385–399 (2009).
[CrossRef]

S. Bobrov, and Y. Y. Schechner, “Image-based prediction of imaging and vision performance,” J. Opt. Soc. Am. A 24, 1920–1929 (2007).
[CrossRef]

Y. Y. Schechner, S. K. Nayar, and P. N. Belhumeur, “Multiplexing for optimal lighting,” IEEE Trans. Pattern Anal. Machine Intell. 29, 1339–1354 (2007).
[CrossRef]

Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar, “Polarization-based vision through haze,” Appl. Opt. 42, 511–525 (2003).
[CrossRef]

T. Treibitz and Y. Y. Schechner, “Recovery limits in pointwise degradation,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2009), p. 1–8.

F. Koreban, and Y. Y. Schechner, “Geometry by deflaring,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2009), p. 1–8.

R. Kaftory, Y. Y. Schechner, and Y. Y. Zeevi, “Variational distance-dependent image restoration,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), pp. 1–8.

Seitz, S. M.

S. M. Seitz, Y. Matsushita, and K. N. Kutulakos, “A theory of inverse light transport,” in Proceedings of IEEE International Conference on Computer Vision (IEEE, 2005), pp. 1440–1447.

Shahram, M.

M. Shahram and P. Milanfar, “Statistical and information-theoretic analysis of resolution in imaging,” IEEE Trans. Inf. Theory 52, 3411–3437 (2006).
[CrossRef]

M. Shahram and P. Milanfar, “Imaging below the diffraction limit: a statistical analysis,” IEEE Trans. Image Process. 13, 677–689 (2004).
[CrossRef]

Shaw, R.

Sheikh, H.

Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[CrossRef]

Simoncelli, E.

Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[CrossRef]

Simoncelli, E. P.

J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Image denoising using scale mixtures of gaussians in the wavelet domain,” IEEE Trans. Image Process. 12, 1338–1351 (2003).
[CrossRef]

Smith, S. W.

S. W. Smith, The Scientist & Engineer’s Guide to Digital Signal Processing (California Tech. Publishing, 1997), Chap. 11.

Spring, K. R.

S. Inoué, and K. R. Spring, Video Microscopy: The Fundamentals, 2nd ed (Springer, 1997), Chap. 7, p. 316.

Steven, A. C.

M. Unser, B. L. Trus, and A. C. Steven, “A new resolution criterion based on spectral signal-to-noise ratios,” Ultramicroscopy 23, 39–51 (1987).
[CrossRef]

Strela, V.

J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Image denoising using scale mixtures of gaussians in the wavelet domain,” IEEE Trans. Image Process. 12, 1338–1351 (2003).
[CrossRef]

Szeliski, R.

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic estimation and removal of noise from a single image,” IEEE Trans. Pattern Anal. Machine Intell. 30, 299–314 (2008).
[CrossRef]

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

Takamatsu, J.

J. Takamatsu, Y. Matsushita, and K. Ikeuchi, “Estimating radiometric response functions from image noise variance,” in Proceedings of European Conference on Computer Vision (Springer, 2008), pp. 623–637.

Tan, K.

Tan, R. T.

R. T. Tan, “Visibility in bad weather from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), p. 108.

Tantalo, T. A.

R. D. Fiete, and T. A. Tantalo, “Comparison of SNR image quality metrics for remote sensing systems,” Opt. Eng. 40, 574–585 (2001).
[CrossRef]

Tchou, C.

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

Toyama, K.

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

Trabka, E.

Treibitz, T.

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Machine Intell. 31, 385–399 (2009).
[CrossRef]

T. Treibitz and Y. Y. Schechner, “Recovery limits in pointwise degradation,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2009), p. 1–8.

Trus, B. L.

M. Unser, B. L. Trus, and A. C. Steven, “A new resolution criterion based on spectral signal-to-noise ratios,” Ultramicroscopy 23, 39–51 (1987).
[CrossRef]

Unger, J.

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

Unser, M.

M. Unser, B. L. Trus, and A. C. Steven, “A new resolution criterion based on spectral signal-to-noise ratios,” Ultramicroscopy 23, 39–51 (1987).
[CrossRef]

Urquijo, S.

Uyttendaele, M.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

Vaish, V.

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

Wainwright, M. J.

J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Image denoising using scale mixtures of gaussians in the wavelet domain,” IEEE Trans. Image Process. 12, 1338–1351 (2003).
[CrossRef]

Wang, C.

S. G. Narasimhan, C. Wang, and S. K. Nayar, “All the images of an outdoor scene,” in Proceedings of European Conference on Computer Vision (IEEE, 2002), pp. 148–162.

Wang, Z.

Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[CrossRef]

Wells, B.

B. Wells, “MTF provides an image-quality metric,” Laser Focus World 41 (2005).

Wenger, A.

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

Zeevi, Y. Y.

R. Kaftory, Y. Y. Schechner, and Y. Y. Zeevi, “Variational distance-dependent image restoration,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), pp. 1–8.

Zitnick, C. L.

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic estimation and removal of noise from a single image,” IEEE Trans. Pattern Anal. Machine Intell. 30, 299–314 (2008).
[CrossRef]

ACM Trans. Graph.

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K. Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph. 23, 664–672 (2004).
[CrossRef]

R. Fattal, “Single image dehazing,” ACM Trans. Graph. 27, 72, (2008).
[CrossRef]

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, “Deep photo: model-based photograph enhancement and viewing,” ACM Trans. Graph. 27, 116 (2008).
[CrossRef]

A. Wenger, A. Gardner, C. Tchou, J. Unger, T. Hawkins, and P. Debevec, “Performance relighting and reflectance transformation with time-multiplexed illumination,” ACM Trans. Graph. 24, 756–764 (2005).
[CrossRef]

S. K. Nayar, G. Krishnan, M. D. Grossberg, and R. Raskar, “Fast separation of direct and global components of a scene using high frequency illumination,” ACM Trans. Graph. 25, 935–944 (2006).
[CrossRef]

M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas, “Synthetic aperture confocal imaging,” ACM Trans. Graph. 23, 825–834 (2004).
[CrossRef]

A. Agrawal, R. Raskar, S. K. Nayar, and Y. Li, “Removing photography artifacts using gradient projection and flash-exposure sampling,” ACM Trans. Graph. 24, 828–835 (2005).
[CrossRef]

R. Mantiuk, K. Kim, A. Rempel, and W. Heidrich, “Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions,” ACM Trans. Graph. 30, 40 (2011).
[CrossRef]

Appl. Opt.

IEEE Trans. Image Process.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3-d transform-domain collaborative filtering,” IEEE Trans. Image Process. 16, 2080–2095 (2007).
[CrossRef]

M. Elad and M. Aharon, “Image denoising via sparse and redundant representations over learned dictionaries,” IEEE Trans. Image Process. 15, 3736–3745 (2006).
[CrossRef]

P. Chatterjee and P. Milanfar, “Clustering-based denoising with locally learned dictionaries,” IEEE Trans. Image Process. 18, 1438–1451 (2009).
[CrossRef]

J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Image denoising using scale mixtures of gaussians in the wavelet domain,” IEEE Trans. Image Process. 12, 1338–1351 (2003).
[CrossRef]

P. Chatterjee and P. Milanfar, “Is denoising dead?,” IEEE Trans. Image Process. 19, 895–911 (2010).
[CrossRef]

M. Shahram and P. Milanfar, “Imaging below the diffraction limit: a statistical analysis,” IEEE Trans. Image Process. 13, 677–689 (2004).
[CrossRef]

Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[CrossRef]

IEEE Trans. Inf. Theory

M. Shahram and P. Milanfar, “Statistical and information-theoretic analysis of resolution in imaging,” IEEE Trans. Inf. Theory 52, 3411–3437 (2006).
[CrossRef]

IEEE Trans. Pattern Anal. Machine Intell.

Y. Y. Schechner, S. K. Nayar, and P. N. Belhumeur, “Multiplexing for optimal lighting,” IEEE Trans. Pattern Anal. Machine Intell. 29, 1339–1354 (2007).
[CrossRef]

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic estimation and removal of noise from a single image,” IEEE Trans. Pattern Anal. Machine Intell. 30, 299–314 (2008).
[CrossRef]

G. E. Healey and R. Kondepudy, “Radiometric CCD camera calibration and noise estimation,” IEEE Trans. Pattern Anal. Machine Intell. 16, 267–276 (1994).
[CrossRef]

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Machine Intell. 31, 385–399 (2009).
[CrossRef]

Int. J. Comput. Vis.

S. K. Nayar, X. S. Fang, and T. Boult, “Separation of reflection components using color and polarization,” Int. J. Comput. Vis. 21, 163–186 (1997).
[CrossRef]

J. Opt. Soc. Am.

J. Opt. Soc. Am. A

J. Soc. Motion Pict. Telev. Eng.

O. Schade, “An evaluation of photographic image quality and resolving power,” J. Soc. Motion Pict. Telev. Eng. 73, 81–119 (1964).

Laser Focus World

B. Wells, “MTF provides an image-quality metric,” Laser Focus World 41 (2005).

Multiscale Model. Simul.

A. Buades, B. Coll, and J. M. Morel, “A review of image denoising algorithms, with a new one,” Multiscale Model. Simul. 4, 490–530 (2005).
[CrossRef]

Opt. Eng.

R. D. Fiete, and T. A. Tantalo, “Comparison of SNR image quality metrics for remote sensing systems,” Opt. Eng. 40, 574–585 (2001).
[CrossRef]

Proc. SPIE

H. Barrett, “NEQ: its progenitors and progeny,” Proc. SPIE 7263, 72630F (2009).

Ultramicroscopy

M. Unser, B. L. Trus, and A. C. Steven, “A new resolution criterion based on spectral signal-to-noise ratios,” Ultramicroscopy 23, 39–51 (1987).
[CrossRef]

Vis. Res.

D. H. Kelly, “Adaptation effects on spatio-temporal sine-wave thresholds,” Vis. Res. 12, 89–101 (1972).
[CrossRef]

Other

S. G. Narasimhan, C. Wang, and S. K. Nayar, “All the images of an outdoor scene,” in Proceedings of European Conference on Computer Vision (IEEE, 2002), pp. 148–162.

B. W. Keelan, Handbook of Image Quality (Dekker, 2002),Chaps. 2, 3.

W. Geisler, Ideal Observer Analysis (MIT Press, 2003), pp. 825–837.

Y. Schechner, D. Diner, and J. Martonchik, “Spaceborne underwater imaging,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2011), p. 1–8.

S. M. Seitz, Y. Matsushita, and K. N. Kutulakos, “A theory of inverse light transport,” in Proceedings of IEEE International Conference on Computer Vision (IEEE, 2005), pp. 1440–1447.

F. Koreban, and Y. Y. Schechner, “Geometry by deflaring,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2009), p. 1–8.

Y. Matsushita, and S. Lin, “Radiometric calibration from noise distributions,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), p. 1–8.

R. Kaftory, Y. Y. Schechner, and Y. Y. Zeevi, “Variational distance-dependent image restoration,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2007), pp. 1–8.

P. Dayan and L. F. Abbott, Theoretical Neuroscience (MIT, 2001), Chap. 4, pp. 139–141.

N. S. Kopeika, A System Engineering Approach to Imaging (SPIE, 1998), Chaps. 9, 10, 19.

S. W. Smith, The Scientist & Engineer’s Guide to Digital Signal Processing (California Tech. Publishing, 1997), Chap. 11.

J. Lloyd, Thermal Imaging Systems (Springer, 1975). Chaps. 5, 10.

J. Takamatsu, Y. Matsushita, and K. Ikeuchi, “Estimating radiometric response functions from image noise variance,” in Proceedings of European Conference on Computer Vision (Springer, 2008), pp. 623–637.

T. J. Fellers, and M. W. Davidson, “CCD noise sources and signal-to-noise ratio,” Optical Microscopy Primer (Molecular Expressions™) (2004).

S. Inoué, and K. R. Spring, Video Microscopy: The Fundamentals, 2nd ed (Springer, 1997), Chap. 7, p. 316.

R. T. Tan, “Visibility in bad weather from a single image,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), p. 108.

J. Gu, R. Ramamoorthi, P. Belhumeur, and S. K. Nayar, “Dirty glass: rendering contamination on transparent surfaces,” in Eurographics Symposium on Rendering (Springer, 2007), p. 159–170.

T. Treibitz and Y. Y. Schechner, “Recovery limits in pointwise degradation,” in Proceedings of IEEE International Conference on Computational Photography (IEEE, 2009), p. 1–8.

A. Levin and B. Nadler, “Natural image denoising: optimality and inherent bounds,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2010), p. 2833–2840.

J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Denoising examples,” decsai.ugr.es/~javier/denoise/examples.

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