M. Makitalo and A. Foi, “Optimal inversion of the generalized anscombe transformation for Poisson-Gaussian noise,” IEEE Trans. Image Process. 22, 91–103 (2013).

[CrossRef]

Y. Han and R. Chen, “Efficient video denoising based on dynamic nonlocal means,” Image Vis. Comput. 30, 78–85 (2012).

[CrossRef]

M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian, “Video denoising, deblocking, and enhancement through separable 4-d nonlocal spatiotemporal transforms,” IEEE Trans. Image Process. 21, 3952–3966 (2012).

[CrossRef]

R. C. Hardie and K. J. Barnard, “Fast super-resolution using an adaptive Wiener filter with robustness to local motion,” Opt. Express 20, 21053–21073 (2012).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

A. Buades, B. Coll, and J.-M. Morel, “Nonlocal image and movie denoising,” Int. J. Comput. Vis. 76, 123–139 (2008).

[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]

R. Hardie, “A fast image super-resolution algorithm using an adaptive Wiener filter,” IEEE Trans. Image Process. 16, 2953–2964 (2007).

[CrossRef]

S. G. Johnson and M. Frigo, “A modified split-radix fft with fewer arithmetic operations,” IEEE Trans. Signal Process. 55, 111–119 (2007).

[CrossRef]

F. Jin, P. Fieguth, and L. Winger, “Wavelet video denoising with regularized multiresolution motion estimation,” EURASIP J. Adv. Signal Process. 2006, 072705 (2006).

[CrossRef]

S. Farsiu, M. Elad, and P. Milanfar, “Video-to-video dynamic super-resolution for grayscale and color sequences,” EURASIP J. Adv. Signal Process. 2006, 061859 (2006).

[CrossRef]

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).

[CrossRef]

R. D. Fiete, “Image quality and λ FN/p for remote sensing systems,” Opt. Eng. 38, 1229–1240 (1999).

[CrossRef]

R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng. 37, 247–260 (1998).

[CrossRef]

J. Kim and J. W. Woods, “Spatiotemporal adaptive 3-d Kalman filter for video,” IEEE Trans. Image Process. 6, 414–424 (1997).

[CrossRef]

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995).

[CrossRef]

S. E. Reichenbach and S. K. Park, “Small convolution kernels for high-fidelity image restoration,” IEEE Trans. Signal Process. 39, 2263–2274 (1991).

[CrossRef]

J. Biemond, J. Rieske, and J. Gerbrands, “A fast Kalman filter for images degraded by both blur and noise,” IEEE Trans. Acoust., Speech, Signal Process. 31, 1248–1256 (1983).

[CrossRef]

R. Dugad and N. Ahuja, “Video denoising by combining Kalman and Wiener estimates,” in Proceedings of the International Conference on Image Processing (ICIP), Kobe (1999), pp. 152–156.

R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng. 37, 247–260 (1998).

[CrossRef]

R. C. Hardie and K. J. Barnard, “Fast super-resolution using an adaptive Wiener filter with robustness to local motion,” Opt. Express 20, 21053–21073 (2012).

[CrossRef]

R. C. Hardie, K. J. Barnard, and R. Ordonez, “Fast super-resolution with affine motion using an adaptive Wiener filter and its application to airborne imaging,” Opt. Express 19, 26208–26231 (2011).

[CrossRef]

R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng. 37, 247–260 (1998).

[CrossRef]

J. Biemond, J. Rieske, and J. Gerbrands, “A fast Kalman filter for images degraded by both blur and noise,” IEEE Trans. Acoust., Speech, Signal Process. 31, 1248–1256 (1983).

[CrossRef]

G. Bishop and G. Welch, “An introduction to the Kalman filter,” Proc. SIGGRAPH, Course 8 (2001).

R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng. 37, 247–260 (1998).

[CrossRef]

M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian, “Video denoising, deblocking, and enhancement through separable 4-d nonlocal spatiotemporal transforms,” IEEE Trans. Image Process. 21, 3952–3966 (2012).

[CrossRef]

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995).

[CrossRef]

A. Buades, B. Coll, and J.-M. Morel, “Nonlocal image and movie denoising,” Int. J. Comput. Vis. 76, 123–139 (2008).

[CrossRef]

Y. Han and R. Chen, “Efficient video denoising based on dynamic nonlocal means,” Image Vis. Comput. 30, 78–85 (2012).

[CrossRef]

A. Buades, B. Coll, and J.-M. Morel, “Nonlocal image and movie denoising,” Int. J. Comput. Vis. 76, 123–139 (2008).

[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]

K. Dabov, A. Foi, and K. Egiazarian, “Video denoising by sparse 3d transform-domain collaborative filtering,” in Proceedings of the 15th European Signal Processing Conference (2007), Vol. 1, p. 145–149.

R. D. Turney, A. M. Reza, and J. G. Delva, “FPGA implementation of adaptive temporal Kalman filter for real time video filtering,” in Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 1999), Vol. 4, pp. 2231–2234.

R. Dugad and N. Ahuja, “Video denoising by combining Kalman and Wiener estimates,” in Proceedings of the International Conference on Image Processing (ICIP), Kobe (1999), pp. 152–156.

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995).

[CrossRef]

M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian, “Video denoising, deblocking, and enhancement through separable 4-d nonlocal spatiotemporal transforms,” IEEE Trans. Image Process. 21, 3952–3966 (2012).

[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]

K. Dabov, A. Foi, and K. Egiazarian, “Video denoising by sparse 3d transform-domain collaborative filtering,” in Proceedings of the 15th European Signal Processing Conference (2007), Vol. 1, p. 145–149.

S. Farsiu, M. Elad, and P. Milanfar, “Video-to-video dynamic super-resolution for grayscale and color sequences,” EURASIP J. Adv. Signal Process. 2006, 061859 (2006).

[CrossRef]

S. Farsiu, M. Elad, and P. Milanfar, “Video-to-video dynamic super-resolution for grayscale and color sequences,” EURASIP J. Adv. Signal Process. 2006, 061859 (2006).

[CrossRef]

F. Jin, P. Fieguth, and L. Winger, “Wavelet video denoising with regularized multiresolution motion estimation,” EURASIP J. Adv. Signal Process. 2006, 072705 (2006).

[CrossRef]

R. D. Fiete, “Image quality and λ FN/p for remote sensing systems,” Opt. Eng. 38, 1229–1240 (1999).

[CrossRef]

M. Makitalo and A. Foi, “Optimal inversion of the generalized anscombe transformation for Poisson-Gaussian noise,” IEEE Trans. Image Process. 22, 91–103 (2013).

[CrossRef]

M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian, “Video denoising, deblocking, and enhancement through separable 4-d nonlocal spatiotemporal transforms,” IEEE Trans. Image Process. 21, 3952–3966 (2012).

[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]

K. Dabov, A. Foi, and K. Egiazarian, “Video denoising by sparse 3d transform-domain collaborative filtering,” in Proceedings of the 15th European Signal Processing Conference (2007), Vol. 1, p. 145–149.

M. Makitalo and A. Foi, “Poisson-Gaussian denoising using the exact unbiased inverse of the generalized anscombe transformation,” in Proceedings of the 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (IEEE, 2012), pp. 1081–1084.

S. G. Johnson and M. Frigo, “A modified split-radix fft with fewer arithmetic operations,” IEEE Trans. Signal Process. 55, 111–119 (2007).

[CrossRef]

J. Biemond, J. Rieske, and J. Gerbrands, “A fast Kalman filter for images degraded by both blur and noise,” IEEE Trans. Acoust., Speech, Signal Process. 31, 1248–1256 (1983).

[CrossRef]

J. Goodman, Introduction to Fourier Optics, 3rd ed. (Roberts & Company, 1968).

Y. Han and R. Chen, “Efficient video denoising based on dynamic nonlocal means,” Image Vis. Comput. 30, 78–85 (2012).

[CrossRef]

R. Hardie, “A fast image super-resolution algorithm using an adaptive Wiener filter,” IEEE Trans. Image Process. 16, 2953–2964 (2007).

[CrossRef]

R. C. Hardie and K. J. Barnard, “Fast super-resolution using an adaptive Wiener filter with robustness to local motion,” Opt. Express 20, 21053–21073 (2012).

[CrossRef]

R. C. Hardie, K. J. Barnard, and R. Ordonez, “Fast super-resolution with affine motion using an adaptive Wiener filter and its application to airborne imaging,” Opt. Express 19, 26208–26231 (2011).

[CrossRef]

R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng. 37, 247–260 (1998).

[CrossRef]

G. Holst and T. Lomheim, CMOS/CCD Sensors and Camera Systems, 2nd ed. (SPIE, 2011).

F. Jin, P. Fieguth, and L. Winger, “Wavelet video denoising with regularized multiresolution motion estimation,” EURASIP J. Adv. Signal Process. 2006, 072705 (2006).

[CrossRef]

S. G. Johnson and M. Frigo, “A modified split-radix fft with fewer arithmetic operations,” IEEE Trans. Signal Process. 55, 111–119 (2007).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).

[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]

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

J. Kim and J. W. Woods, “Spatiotemporal adaptive 3-d Kalman filter for video,” IEEE Trans. Image Process. 6, 414–424 (1997).

[CrossRef]

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995).

[CrossRef]

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995).

[CrossRef]

G. Holst and T. Lomheim, CMOS/CCD Sensors and Camera Systems, 2nd ed. (SPIE, 2011).

M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian, “Video denoising, deblocking, and enhancement through separable 4-d nonlocal spatiotemporal transforms,” IEEE Trans. Image Process. 21, 3952–3966 (2012).

[CrossRef]

M. A. Makar and H. K. Raghunandan, “Wiener and Kalman filters for denoising video signals,” EE378 Class Project, Spring (2008).

M. Makitalo and A. Foi, “Optimal inversion of the generalized anscombe transformation for Poisson-Gaussian noise,” IEEE Trans. Image Process. 22, 91–103 (2013).

[CrossRef]

M. Makitalo and A. Foi, “Poisson-Gaussian denoising using the exact unbiased inverse of the generalized anscombe transformation,” in Proceedings of the 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (IEEE, 2012), pp. 1081–1084.

S. Farsiu, M. Elad, and P. Milanfar, “Video-to-video dynamic super-resolution for grayscale and color sequences,” EURASIP J. Adv. Signal Process. 2006, 061859 (2006).

[CrossRef]

A. Buades, B. Coll, and J.-M. Morel, “Nonlocal image and movie denoising,” Int. J. Comput. Vis. 76, 123–139 (2008).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).

[CrossRef]

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).

[CrossRef]

S. E. Reichenbach and S. K. Park, “Small convolution kernels for high-fidelity image restoration,” IEEE Trans. Signal Process. 39, 2263–2274 (1991).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

M. A. Makar and H. K. Raghunandan, “Wiener and Kalman filters for denoising video signals,” EE378 Class Project, Spring (2008).

S. E. Reichenbach and S. K. Park, “Small convolution kernels for high-fidelity image restoration,” IEEE Trans. Signal Process. 39, 2263–2274 (1991).

[CrossRef]

R. D. Turney, A. M. Reza, and J. G. Delva, “FPGA implementation of adaptive temporal Kalman filter for real time video filtering,” in Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 1999), Vol. 4, pp. 2231–2234.

J. Biemond, J. Rieske, and J. Gerbrands, “A fast Kalman filter for images degraded by both blur and noise,” IEEE Trans. Acoust., Speech, Signal Process. 31, 1248–1256 (1983).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

R. D. Turney, A. M. Reza, and J. G. Delva, “FPGA implementation of adaptive temporal Kalman filter for real time video filtering,” in Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 1999), Vol. 4, pp. 2231–2234.

R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng. 37, 247–260 (1998).

[CrossRef]

G. Bishop and G. Welch, “An introduction to the Kalman filter,” Proc. SIGGRAPH, Course 8 (2001).

F. Jin, P. Fieguth, and L. Winger, “Wavelet video denoising with regularized multiresolution motion estimation,” EURASIP J. Adv. Signal Process. 2006, 072705 (2006).

[CrossRef]

J. Kim and J. W. Woods, “Spatiotemporal adaptive 3-d Kalman filter for video,” IEEE Trans. Image Process. 6, 414–424 (1997).

[CrossRef]

F. Jin, P. Fieguth, and L. Winger, “Wavelet video denoising with regularized multiresolution motion estimation,” EURASIP J. Adv. Signal Process. 2006, 072705 (2006).

[CrossRef]

S. Farsiu, M. Elad, and P. Milanfar, “Video-to-video dynamic super-resolution for grayscale and color sequences,” EURASIP J. Adv. Signal Process. 2006, 061859 (2006).

[CrossRef]

S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21–36 (2003).

[CrossRef]

J. Biemond, J. Rieske, and J. Gerbrands, “A fast Kalman filter for images degraded by both blur and noise,” IEEE Trans. Acoust., Speech, Signal Process. 31, 1248–1256 (1983).

[CrossRef]

L. Jovanov, A. Pizurica, S. Schulte, P. Schelkens, A. Munteanu, E. Kerre, and W. Philips, “Combined wavelet-domain and motion-compensated video denoising based on video codec motion estimation methods,” IEEE Trans. Circuits Syst. Video Technol. 19, 417–421 (2009).

[CrossRef]

R. Hardie, “A fast image super-resolution algorithm using an adaptive Wiener filter,” IEEE Trans. Image Process. 16, 2953–2964 (2007).

[CrossRef]

J. Kim and J. W. Woods, “Spatiotemporal adaptive 3-d Kalman filter for video,” IEEE Trans. Image Process. 6, 414–424 (1997).

[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]

M. Maggioni, G. Boracchi, A. Foi, and K. Egiazarian, “Video denoising, deblocking, and enhancement through separable 4-d nonlocal spatiotemporal transforms,” IEEE Trans. Image Process. 21, 3952–3966 (2012).

[CrossRef]

M. Makitalo and A. Foi, “Optimal inversion of the generalized anscombe transformation for Poisson-Gaussian noise,” IEEE Trans. Image Process. 22, 91–103 (2013).

[CrossRef]

S. E. Reichenbach and S. K. Park, “Small convolution kernels for high-fidelity image restoration,” IEEE Trans. Signal Process. 39, 2263–2274 (1991).

[CrossRef]

S. G. Johnson and M. Frigo, “A modified split-radix fft with fewer arithmetic operations,” IEEE Trans. Signal Process. 55, 111–119 (2007).

[CrossRef]

Y. Han and R. Chen, “Efficient video denoising based on dynamic nonlocal means,” Image Vis. Comput. 30, 78–85 (2012).

[CrossRef]

A. Buades, B. Coll, and J.-M. Morel, “Nonlocal image and movie denoising,” Int. J. Comput. Vis. 76, 123–139 (2008).

[CrossRef]

R. D. Fiete, “Image quality and λ FN/p for remote sensing systems,” Opt. Eng. 38, 1229–1240 (1999).

[CrossRef]

R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng. 37, 247–260 (1998).

[CrossRef]

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, “Noise reduction filters for dynamic image sequences: a review,” Proc. IEEE 83, 1272–1292 (1995).

[CrossRef]

M. A. Makar and H. K. Raghunandan, “Wiener and Kalman filters for denoising video signals,” EE378 Class Project, Spring (2008).

G. Bishop and G. Welch, “An introduction to the Kalman filter,” Proc. SIGGRAPH, Course 8 (2001).

M. Makitalo and A. Foi, “Poisson-Gaussian denoising using the exact unbiased inverse of the generalized anscombe transformation,” in Proceedings of the 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (IEEE, 2012), pp. 1081–1084.

R. Dugad and N. Ahuja, “Video denoising by combining Kalman and Wiener estimates,” in Proceedings of the International Conference on Image Processing (ICIP), Kobe (1999), pp. 152–156.

R. D. Turney, A. M. Reza, and J. G. Delva, “FPGA implementation of adaptive temporal Kalman filter for real time video filtering,” in Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 1999), Vol. 4, pp. 2231–2234.

K. Dabov, A. Foi, and K. Egiazarian, “Video denoising by sparse 3d transform-domain collaborative filtering,” in Proceedings of the 15th European Signal Processing Conference (2007), Vol. 1, p. 145–149.

G. Holst and T. Lomheim, CMOS/CCD Sensors and Camera Systems, 2nd ed. (SPIE, 2011).

J. Goodman, Introduction to Fourier Optics, 3rd ed. (Roberts & Company, 1968).