references

References

[R303]

François Orieux, Jean-François Giovannelli, and Thomas Rodet, “Bayesian estimation of regularization and point spread function parameters for Wiener-Hunt deconvolution”, J. Opt. Soc. Am. A 27, 1593-1607 (2010)

http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-27-7-1593

[R304]

Richardson, William Hadley, “Bayesian-Based Iterative Method of Image Restoration”. JOSA 62 (1): 55–59. doi:10.1364/JOSA.62.000055, 1972

[R305]

B. R. Hunt “A matrix theory proof of the discrete convolution theorem”, IEEE Trans. on Audio and Electroacoustics, vol. au-19, no. 4, pp. 285-288, dec. 1971

`skimage.restoration.denoise_bilateral`(image)	Denoise image using bilateral filter.
`skimage.restoration.denoise_nl_means`(image)	Perform non-local means denoising on 2-D or 3-D grayscale images, and 2-D RGB images.
`skimage.restoration.denoise_tv_bregman`(...)	Perform total-variation denoising using split-Bregman optimization.
`skimage.restoration.denoise_tv_chambolle`(im)	Perform total-variation denoising on n-dimensional images.
`skimage.restoration.nl_means_denoising`(...)	Deprecated function. Use `skimage.restoration.denoise_nl_means` instead.
`skimage.restoration.richardson_lucy`(image, psf)	Richardson-Lucy deconvolution.
`skimage.restoration.unsupervised_wiener`(...)	Unsupervised Wiener-Hunt deconvolution.
`skimage.restoration.unwrap_phase`(image[, ...])	Recover the original from a wrapped phase image.
`skimage.restoration.wiener`(image, psf, balance)	Wiener-Hunt deconvolution

Links:

http://scikit-image.org/docs/0.12.x/api/skimage.restoration.html#references

doc_scikit_image

2025-01-10 15:47:30

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