Abstract

We demonstrate the effectiveness of the nonlocal means (NLM) filter for speckle denoising in digital holography. The speckle noise adapted version of the NLM filter is compared with other common speckle denoising filters and is found to give better visual and quantitative results.

© 2012 Optical Society of America

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References

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  1. J. W. Goodman, Speckle Phenomena: Theory and Applications (Roberts, 2006).
  2. J. W. Goodman and R. W. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett. 11, 77–79 (1967).
    [CrossRef]
  3. T. Huang, “Digital holography,” Proc. IEEE 59, 1335–1346 (1971).
    [CrossRef]
  4. F. Dubois, L. Joannes, and J.-C. Legros, “Improved three-dimensional imaging with a digital holography microscope with a source of partial spatial coherence,” Appl. Opt. 38, 7085–7094 (1999).
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  6. L. Yaroslavsky, Digital Holography and Digital Image Processing, Principles, Methods, Algorithms (Kluwer, 2004), pp. 72–77, 305–312.
  7. J. Garcia-Sucerquia, J. A. H. Ramirez, and D. V. Prieto, “Reduction of speckle noise in digital holography by using digital image processing,” Optik 116, 44–48 (2005).
    [CrossRef]
  8. S. Mirza, R. Kumar, and C. Shakher, “Study of various preprocessing schemes and wavelet filters for speckle noise reduction in digital speckle pattern interferometric fringes,” Opt. Eng. 44, 045603 (2005).
    [CrossRef]
  9. P. Almoro, G. Pedrini, and W. Osten, “Aperture synthesis in phase retrieval using a volume-speckle field,” Opt. Lett. 32, 733–735 (2007).
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  10. J. Maycock, B. M. Hennelly, J. B. McDonald, Y. Frauel, A. Castro, B. Javidi, and T. J. Naughton, “Reduction of speckle in digital holography by discrete Fourier filtering,” J. Opt. Soc. Am. A 24, 1617–1622 (2007).
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  11. T. Nomura, M. Okamura, E. Nitanai, and T. Numata, “Image quality improvement of digital holography by superposition of reconstructed images obtained by multiple wavelengths,” Appl. Opt. 47, D38–D43 (2008).
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  12. P. Feng, X. Wen, and R. Lu, “Long-working-distance synthetic aperture Fresnel off-axis digital holography,” Opt. Express 17, 5473–5480 (2009).
    [CrossRef]
  13. Y. K. Park, W. Choi, Z. Yaqoob, R. Dasari, K. Badizadegan, and M. S. Feld, “Speckle-field digital holographic microscopy,” Opt. Express 17, 12285–12292 (2009).
    [CrossRef]
  14. S. Hertwig, H. Babovsky, A. Kiessling, and R. Kowarschik, “Reduction of speckles in digital holographic interferometry,” in Fringe 2009, W. Osten and M. Kujawinska, eds. (Springer, 2009), pp. 184–188.
  15. L. Rong, W. Xiao, F. Pan, S. Liu, and R. Li, “Speckle noise reduction in digital holography by use of multiple polarization holograms,” Chin. Opt. Lett. 8, 653–655 (2010).
    [CrossRef]
  16. M. Kim, Y. Choi, C. Fang-Yen, Y. Sung, R. R. Dasari, M. S. Feld, and W. Choi, “High-speed synthetic aperture microscopy for live cell imaging,” Opt. Lett. 36, 148–150 (2011).
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  18. V. Micó, C. Ferreira, and J. García, “Surpassing digital holography limits by lensless object scanning holography,” Opt. Express 20, 9382–9395 (2012).
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  19. J. S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Trans. Pattern Anal. Machine Intell. 2, 165–168 (1980).
    [CrossRef]
  20. D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise”, IEEE Trans. Pattern Anal. Machine Intell. 7, 165–177 (1985).
    [CrossRef]
  21. V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application to adaptive digital filtering of multiplicative noise,” IEEE Trans. Pattern Anal. Machine Intell. 4, 157–166 (1982).
    [CrossRef]
  22. C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” presented at Sixth International Conference on Computer Vision, Bombay, 4–7 Jan. 1998.
  23. G. S. S Sudha and R Sukanesh, “Speckle noise reduction in ultrasound images using context-based adaptive wavelet thresholding,” IETE J. Res. 55, 135–143 (2009).
    [CrossRef]
  24. A. Buades, B. Coll, and J.-M. Morel, “A non-local algorithm for image denoising,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 60–65.
  25. P. Coupe, P. Hellier, C. Kervrann, and C. Barillot, “Nonlocal means-based speckle filtering for ultrasound images,” IEEE Trans. Image Process. 18, 2221–2229 (2009).
    [CrossRef]
  26. C. Kervrann, J. Boulanger, and P. Coupé, “Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal,” in Proceedings of the 1st International Conference on Scale Space and Variational Methods in Computer Vision (Springer-Verlag, 2007), pp. 520–532.
  27. J. Salmon, “On two parameters for denoising with non-local means,” IEEE Signal Process. Lett. 17, 269–272 (2010).
    [CrossRef]
  28. I. Yamaguchi and T. Zhang, “Phase-shifting digital holography,” Opt. Lett. 22, 1268–1270 (1997).
    [CrossRef]
  29. A. Shamsoddini and J. C. Trinder, “Image texture preservation in speckle noise suppression,” presented at ISPRS TC VII Symposium—100 Years ISPRS, Vienna, Austria, 5–7 July 2010.
  30. G. H. Sendra, H. J. Rabal, M. Trivi, and R. Arizaga, “Numerical model for simulation of dynamic speckle reference patterns,” Opt. Commun. 282, 3693–3700 (2009).
    [CrossRef]
  31. Available at http://wintech-nano.com/services_ic_SignalTapout/ .

2012

2011

2010

2009

G. H. Sendra, H. J. Rabal, M. Trivi, and R. Arizaga, “Numerical model for simulation of dynamic speckle reference patterns,” Opt. Commun. 282, 3693–3700 (2009).
[CrossRef]

G. S. S Sudha and R Sukanesh, “Speckle noise reduction in ultrasound images using context-based adaptive wavelet thresholding,” IETE J. Res. 55, 135–143 (2009).
[CrossRef]

P. Coupe, P. Hellier, C. Kervrann, and C. Barillot, “Nonlocal means-based speckle filtering for ultrasound images,” IEEE Trans. Image Process. 18, 2221–2229 (2009).
[CrossRef]

P. Feng, X. Wen, and R. Lu, “Long-working-distance synthetic aperture Fresnel off-axis digital holography,” Opt. Express 17, 5473–5480 (2009).
[CrossRef]

Y. K. Park, W. Choi, Z. Yaqoob, R. Dasari, K. Badizadegan, and M. S. Feld, “Speckle-field digital holographic microscopy,” Opt. Express 17, 12285–12292 (2009).
[CrossRef]

2008

2007

2005

J. Garcia-Sucerquia, J. A. H. Ramirez, and D. V. Prieto, “Reduction of speckle noise in digital holography by using digital image processing,” Optik 116, 44–48 (2005).
[CrossRef]

S. Mirza, R. Kumar, and C. Shakher, “Study of various preprocessing schemes and wavelet filters for speckle noise reduction in digital speckle pattern interferometric fringes,” Opt. Eng. 44, 045603 (2005).
[CrossRef]

2002

1999

1997

1985

D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise”, IEEE Trans. Pattern Anal. Machine Intell. 7, 165–177 (1985).
[CrossRef]

1982

V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application to adaptive digital filtering of multiplicative noise,” IEEE Trans. Pattern Anal. Machine Intell. 4, 157–166 (1982).
[CrossRef]

1980

J. S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Trans. Pattern Anal. Machine Intell. 2, 165–168 (1980).
[CrossRef]

1971

T. Huang, “Digital holography,” Proc. IEEE 59, 1335–1346 (1971).
[CrossRef]

1967

J. W. Goodman and R. W. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett. 11, 77–79 (1967).
[CrossRef]

Almoro, P.

Arizaga, R.

G. H. Sendra, H. J. Rabal, M. Trivi, and R. Arizaga, “Numerical model for simulation of dynamic speckle reference patterns,” Opt. Commun. 282, 3693–3700 (2009).
[CrossRef]

Babovsky, H.

S. Hertwig, H. Babovsky, A. Kiessling, and R. Kowarschik, “Reduction of speckles in digital holographic interferometry,” in Fringe 2009, W. Osten and M. Kujawinska, eds. (Springer, 2009), pp. 184–188.

Badizadegan, K.

Barillot, C.

P. Coupe, P. Hellier, C. Kervrann, and C. Barillot, “Nonlocal means-based speckle filtering for ultrasound images,” IEEE Trans. Image Process. 18, 2221–2229 (2009).
[CrossRef]

Boulanger, J.

C. Kervrann, J. Boulanger, and P. Coupé, “Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal,” in Proceedings of the 1st International Conference on Scale Space and Variational Methods in Computer Vision (Springer-Verlag, 2007), pp. 520–532.

Buades, A.

A. Buades, B. Coll, and J.-M. Morel, “A non-local algorithm for image denoising,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 60–65.

Castro, A.

Chavel, P.

D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise”, IEEE Trans. Pattern Anal. Machine Intell. 7, 165–177 (1985).
[CrossRef]

Choi, W.

Choi, Y.

Coll, B.

A. Buades, B. Coll, and J.-M. Morel, “A non-local algorithm for image denoising,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 60–65.

Coupe, P.

P. Coupe, P. Hellier, C. Kervrann, and C. Barillot, “Nonlocal means-based speckle filtering for ultrasound images,” IEEE Trans. Image Process. 18, 2221–2229 (2009).
[CrossRef]

Coupé, P.

C. Kervrann, J. Boulanger, and P. Coupé, “Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal,” in Proceedings of the 1st International Conference on Scale Space and Variational Methods in Computer Vision (Springer-Verlag, 2007), pp. 520–532.

Dasari, R.

Dasari, R. R.

Dubois, F.

Fang-Yen, C.

Feld, M. S.

Feng, P.

Ferreira, C.

Frauel, Y.

Frost, V. S.

V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application to adaptive digital filtering of multiplicative noise,” IEEE Trans. Pattern Anal. Machine Intell. 4, 157–166 (1982).
[CrossRef]

García, J.

Garcia-Sucerquia, J.

J. Garcia-Sucerquia, J. A. H. Ramirez, and D. V. Prieto, “Reduction of speckle noise in digital holography by using digital image processing,” Optik 116, 44–48 (2005).
[CrossRef]

Goodman, J. W.

J. W. Goodman and R. W. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett. 11, 77–79 (1967).
[CrossRef]

J. W. Goodman, Speckle Phenomena: Theory and Applications (Roberts, 2006).

Hellier, P.

P. Coupe, P. Hellier, C. Kervrann, and C. Barillot, “Nonlocal means-based speckle filtering for ultrasound images,” IEEE Trans. Image Process. 18, 2221–2229 (2009).
[CrossRef]

Hennelly, B. M.

Hertwig, S.

S. Hertwig, H. Babovsky, A. Kiessling, and R. Kowarschik, “Reduction of speckles in digital holographic interferometry,” in Fringe 2009, W. Osten and M. Kujawinska, eds. (Springer, 2009), pp. 184–188.

Holtzman, J. C.

V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application to adaptive digital filtering of multiplicative noise,” IEEE Trans. Pattern Anal. Machine Intell. 4, 157–166 (1982).
[CrossRef]

Huang, T.

T. Huang, “Digital holography,” Proc. IEEE 59, 1335–1346 (1971).
[CrossRef]

Javidi, B.

Joannes, L.

Kervrann, C.

P. Coupe, P. Hellier, C. Kervrann, and C. Barillot, “Nonlocal means-based speckle filtering for ultrasound images,” IEEE Trans. Image Process. 18, 2221–2229 (2009).
[CrossRef]

C. Kervrann, J. Boulanger, and P. Coupé, “Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal,” in Proceedings of the 1st International Conference on Scale Space and Variational Methods in Computer Vision (Springer-Verlag, 2007), pp. 520–532.

Kiessling, A.

S. Hertwig, H. Babovsky, A. Kiessling, and R. Kowarschik, “Reduction of speckles in digital holographic interferometry,” in Fringe 2009, W. Osten and M. Kujawinska, eds. (Springer, 2009), pp. 184–188.

Kim, M.

Kowarschik, R.

S. Hertwig, H. Babovsky, A. Kiessling, and R. Kowarschik, “Reduction of speckles in digital holographic interferometry,” in Fringe 2009, W. Osten and M. Kujawinska, eds. (Springer, 2009), pp. 184–188.

Kuan, D. T.

D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise”, IEEE Trans. Pattern Anal. Machine Intell. 7, 165–177 (1985).
[CrossRef]

Kumar, R.

S. Mirza, R. Kumar, and C. Shakher, “Study of various preprocessing schemes and wavelet filters for speckle noise reduction in digital speckle pattern interferometric fringes,” Opt. Eng. 44, 045603 (2005).
[CrossRef]

Lawrence, R. W.

J. W. Goodman and R. W. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett. 11, 77–79 (1967).
[CrossRef]

Lee, J. S.

J. S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Trans. Pattern Anal. Machine Intell. 2, 165–168 (1980).
[CrossRef]

Legros, J.-C.

Li, R.

Liu, S.

Lu, R.

Manduchi, R.

C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” presented at Sixth International Conference on Computer Vision, Bombay, 4–7 Jan. 1998.

Massig, J. H.

Maycock, J.

McDonald, J. B.

Micó, V.

Mirza, S.

S. Mirza, R. Kumar, and C. Shakher, “Study of various preprocessing schemes and wavelet filters for speckle noise reduction in digital speckle pattern interferometric fringes,” Opt. Eng. 44, 045603 (2005).
[CrossRef]

Morel, J.-M.

A. Buades, B. Coll, and J.-M. Morel, “A non-local algorithm for image denoising,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 60–65.

Naughton, T. J.

Nitanai, E.

Nomura, T.

Numata, T.

Okamura, M.

Osten, W.

Pan, F.

Park, Y. K.

Pedrini, G.

Prieto, D. V.

J. Garcia-Sucerquia, J. A. H. Ramirez, and D. V. Prieto, “Reduction of speckle noise in digital holography by using digital image processing,” Optik 116, 44–48 (2005).
[CrossRef]

Rabal, H. J.

G. H. Sendra, H. J. Rabal, M. Trivi, and R. Arizaga, “Numerical model for simulation of dynamic speckle reference patterns,” Opt. Commun. 282, 3693–3700 (2009).
[CrossRef]

Ramirez, J. A. H.

J. Garcia-Sucerquia, J. A. H. Ramirez, and D. V. Prieto, “Reduction of speckle noise in digital holography by using digital image processing,” Optik 116, 44–48 (2005).
[CrossRef]

Rong, L.

Salmon, J.

J. Salmon, “On two parameters for denoising with non-local means,” IEEE Signal Process. Lett. 17, 269–272 (2010).
[CrossRef]

Sawchuk, A. A.

D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise”, IEEE Trans. Pattern Anal. Machine Intell. 7, 165–177 (1985).
[CrossRef]

Sendra, G. H.

G. H. Sendra, H. J. Rabal, M. Trivi, and R. Arizaga, “Numerical model for simulation of dynamic speckle reference patterns,” Opt. Commun. 282, 3693–3700 (2009).
[CrossRef]

Shakher, C.

S. Mirza, R. Kumar, and C. Shakher, “Study of various preprocessing schemes and wavelet filters for speckle noise reduction in digital speckle pattern interferometric fringes,” Opt. Eng. 44, 045603 (2005).
[CrossRef]

Shamsoddini, A.

A. Shamsoddini and J. C. Trinder, “Image texture preservation in speckle noise suppression,” presented at ISPRS TC VII Symposium—100 Years ISPRS, Vienna, Austria, 5–7 July 2010.

Shanmugan, K. S.

V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application to adaptive digital filtering of multiplicative noise,” IEEE Trans. Pattern Anal. Machine Intell. 4, 157–166 (1982).
[CrossRef]

Stiles, J. A.

V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application to adaptive digital filtering of multiplicative noise,” IEEE Trans. Pattern Anal. Machine Intell. 4, 157–166 (1982).
[CrossRef]

Strand, T. C.

D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise”, IEEE Trans. Pattern Anal. Machine Intell. 7, 165–177 (1985).
[CrossRef]

Sudha, G. S. S

G. S. S Sudha and R Sukanesh, “Speckle noise reduction in ultrasound images using context-based adaptive wavelet thresholding,” IETE J. Res. 55, 135–143 (2009).
[CrossRef]

Sukanesh, R

G. S. S Sudha and R Sukanesh, “Speckle noise reduction in ultrasound images using context-based adaptive wavelet thresholding,” IETE J. Res. 55, 135–143 (2009).
[CrossRef]

Sung, Y.

Tomasi, C.

C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” presented at Sixth International Conference on Computer Vision, Bombay, 4–7 Jan. 1998.

Trinder, J. C.

A. Shamsoddini and J. C. Trinder, “Image texture preservation in speckle noise suppression,” presented at ISPRS TC VII Symposium—100 Years ISPRS, Vienna, Austria, 5–7 July 2010.

Trivi, M.

G. H. Sendra, H. J. Rabal, M. Trivi, and R. Arizaga, “Numerical model for simulation of dynamic speckle reference patterns,” Opt. Commun. 282, 3693–3700 (2009).
[CrossRef]

Wang, F. J.

Wen, X.

Xiao, W.

Yamaguchi, I.

Yaqoob, Z.

Yaroslavsky, L.

L. Yaroslavsky, Digital Holography and Digital Image Processing, Principles, Methods, Algorithms (Kluwer, 2004), pp. 72–77, 305–312.

Zhang, T.

Appl. Opt.

Appl. Phys. Lett.

J. W. Goodman and R. W. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett. 11, 77–79 (1967).
[CrossRef]

Chin. Opt. Lett.

IEEE Signal Process. Lett.

J. Salmon, “On two parameters for denoising with non-local means,” IEEE Signal Process. Lett. 17, 269–272 (2010).
[CrossRef]

IEEE Trans. Image Process.

P. Coupe, P. Hellier, C. Kervrann, and C. Barillot, “Nonlocal means-based speckle filtering for ultrasound images,” IEEE Trans. Image Process. 18, 2221–2229 (2009).
[CrossRef]

IEEE Trans. Pattern Anal. Machine Intell.

J. S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Trans. Pattern Anal. Machine Intell. 2, 165–168 (1980).
[CrossRef]

D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise”, IEEE Trans. Pattern Anal. Machine Intell. 7, 165–177 (1985).
[CrossRef]

V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application to adaptive digital filtering of multiplicative noise,” IEEE Trans. Pattern Anal. Machine Intell. 4, 157–166 (1982).
[CrossRef]

IETE J. Res.

G. S. S Sudha and R Sukanesh, “Speckle noise reduction in ultrasound images using context-based adaptive wavelet thresholding,” IETE J. Res. 55, 135–143 (2009).
[CrossRef]

J. Opt. Soc. Am. A

Opt. Commun.

G. H. Sendra, H. J. Rabal, M. Trivi, and R. Arizaga, “Numerical model for simulation of dynamic speckle reference patterns,” Opt. Commun. 282, 3693–3700 (2009).
[CrossRef]

Opt. Eng.

S. Mirza, R. Kumar, and C. Shakher, “Study of various preprocessing schemes and wavelet filters for speckle noise reduction in digital speckle pattern interferometric fringes,” Opt. Eng. 44, 045603 (2005).
[CrossRef]

Opt. Express

Opt. Lett.

Optik

J. Garcia-Sucerquia, J. A. H. Ramirez, and D. V. Prieto, “Reduction of speckle noise in digital holography by using digital image processing,” Optik 116, 44–48 (2005).
[CrossRef]

Proc. IEEE

T. Huang, “Digital holography,” Proc. IEEE 59, 1335–1346 (1971).
[CrossRef]

Other

L. Yaroslavsky, Digital Holography and Digital Image Processing, Principles, Methods, Algorithms (Kluwer, 2004), pp. 72–77, 305–312.

J. W. Goodman, Speckle Phenomena: Theory and Applications (Roberts, 2006).

S. Hertwig, H. Babovsky, A. Kiessling, and R. Kowarschik, “Reduction of speckles in digital holographic interferometry,” in Fringe 2009, W. Osten and M. Kujawinska, eds. (Springer, 2009), pp. 184–188.

A. Shamsoddini and J. C. Trinder, “Image texture preservation in speckle noise suppression,” presented at ISPRS TC VII Symposium—100 Years ISPRS, Vienna, Austria, 5–7 July 2010.

Available at http://wintech-nano.com/services_ic_SignalTapout/ .

A. Buades, B. Coll, and J.-M. Morel, “A non-local algorithm for image denoising,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 60–65.

C. Kervrann, J. Boulanger, and P. Coupé, “Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal,” in Proceedings of the 1st International Conference on Scale Space and Variational Methods in Computer Vision (Springer-Verlag, 2007), pp. 520–532.

C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” presented at Sixth International Conference on Computer Vision, Bombay, 4–7 Jan. 1998.

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Figures (3)

Fig. 1.
Fig. 1.

Illustration of the NLM filter windows. The search window is the entire image, while p is the window of interest, which is the central pixel we wish to denoise. The windows q 1 , q 2 , and q 3 are the similarity windows.

Fig. 2.
Fig. 2.

Comparison of speckle reduction filters applied on an object’s image, which was reconstructed from its digital holographic recording: (a) back propagation from the original hologram, (b) denoised with median filter, (c) denoised with Frost filter, (d) denoised with Lee filter, (e) denoised with bilateral filter, (f) denoised with WT filter, (g) denoised with NLM filter.

Fig. 3.
Fig. 3.

Simulation results: (a) and (d) original images, (b) and (e) noisy images, (c) and (f) respective denoised images using NLM.

Tables (2)

Tables Icon

Table 1. Performance Comparison Between NLM, Median, Lee, Frost, Bilateral, and Wavelet Thresholding Filters for the Digitally Holographic Recorded Cube Object of Fig. 2a

Tables Icon

Table 2. Performance Comparison (in terms of PSNR improvement) Between NLM, Median, Lee, Frost, Bilateral, and Wavelet Thresholding Filters for Electronic Chip and Coins Imagesa

Equations (6)

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

u out ( x i , y i ) = x j , y j Ω dim w ( x j , y j ) · u ( x j , y j ) ,
w ( x j , y j ) = 1 Z i exp [ u ( N i ) u ( N j ) 2 , a 2 h 2 ] ,
w ( x j , y j ) = 1 Z i exp [ u ( N i ) u ( N j ) 2 , a 2 u ( N j ) 2 γ ] ,
ENL = ( mean std ) 2 ,
SSI = std ( I f ) mean ( I f ) · mean ( I o ) std ( I o ) ,
SMPI = ( 1 + | mean ( I f ) mean ( I o ) | ) · std ( I f ) std ( I o ) .

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