Results 191 to 200 of about 323,867 (242)

Ratio Quantification of Geranium and Rose Essential Oil Mixtures via Deep Learning Analysis of Complex Raman Spectra. [PDF]

ACS Meas Sci Au
Tang JW, Hong YX, Chen J, Xie YY, Ma ZW, Liu QH, Wang L.   +6 more
europepmc   +1 more source

Joint estimation of point spread function and molecule positions in SMLM informed from multiple planes. [PDF]

Biomed Opt Express
Maloberti JG, Velas L, Moser S, Gaugutz A, Bishara M, Schütz GJ, Jesacher A.   +6 more
europepmc   +1 more source

Histopathological evaluation of facial melasma treated with oral tranexamic acid alone and in combination with ketotifen. [PDF]

An Bras Dermatol
Cruz ACL, Cassiano DP, Miot HA, Espósito ACC, Hassum K, de Brito MB, E Silva Enokihara MMS, Lima Constantino MCC, Bottura HR, de Almeida JS, Bagatin E.   +10 more
europepmc   +1 more source

Efficacy inference in early-phase non-controlled clinical trials via Bayesian biomarker deconvolution

Humphries C, Kilpatrick AM, Cartwright JA, Potter C, Fernando AJ, Candela ME, Man J, Aird R, Simpson KJ, Lyall MJ, Lewis PS, Rodriguez A, Weir CJ, Dear JW, Forbes SJ, Schumacher LJ.   +15 more
europepmc   +1 more source

Normalized Blind Deconvolution [PDF]

, 2018
We introduce a family of novel approaches to single-image blind deconvolution, i.e., the problem of recovering a sharp image and a blur kernel from a single blurry input. This problem is highly ill-posed, because infinite (image, blur) pairs produce the same blurry image.
Meiguang Jin, Stefan Roth 0001, Paolo Favaro   +2 more
openaire   +4 more sources

Some of the next articles are maybe not open access.

Related searches:

Blind image deconvolution

IEEE Signal Processing Magazine, 1996
The goal of image restoration is to reconstruct the original scene from a degraded observation. This recovery process is critical to many image processing applications. Although classical linear image restoration has been thoroughly studied, the more difficult problem of blind image restoration has numerous research possibilities.
Deepa Kundur
exaly   +3 more sources

Blind image deconvolution revisited

IEEE Signal Processing Magazine, 1996
The article discusses the major approaches, such as projection based blind deconvolution and maximum likelihood restoration, we overlooked previously (see ibid., no.5, 1996). We discuss them for completeness along with some other works found in the literature.
Deepa Kundur
exaly   +3 more sources

Understanding Blind Deconvolution Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011
Blind deconvolution is the recovery of a sharp version of a blurred image when the blur kernel is unknown. Recent algorithms have afforded dramatic progress, yet many aspects of the problem remain challenging and hard to understand. The goal of this paper is to analyze and evaluate recent blind deconvolution algorithms both theoretically and ...
William T Freeman, Anat Levin, Yair Weiss   +2 more
exaly   +4 more sources

Contrasts for multichannel blind deconvolution

IEEE Signal Processing Letters, 1996
A class of optimization criteria is proposed whose maximization allows us to carry out blind multichannel deconvolution in the presence of additive noise. Contrasts presented in the paper encompass those related to source separation and independent component analysis problems.
exaly   +3 more sources

Superresolution and blind deconvolution of video

2008 19th International Conference on Pattern Recognition, 2008
In many real applications traditional superresolution methods fail to provide high-resolution images due to objectionable blur and inaccurate registration of input low-resolution images. In this paper, we present a method of superresolution and blind deconvolution of video sequences and address problems of misregistration, local motion and change of ...
Filip Sroubek, Jan Flusser, Michal Sorel
openaire   +2 more sources