Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Suhail S. Saquib"'
Autor:
Suhail S. Saquib, Brian Busch
Publikováno v:
NIP & Digital Fabrication Conference. 21:211-214
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adbe3b47bbaa98495c0fe86bab1384b4
https://doi.org/10.2352/issn.2169-4451.2005.21.1.art00060_1
https://doi.org/10.2352/issn.2169-4451.2005.21.1.art00060_1
Publikováno v:
NIP & Digital Fabrication Conference. 18:200-204
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2aadd8ea06555a9115390d12198574b
https://doi.org/10.2352/issn.2169-4451.2002.18.1.art00048_1
https://doi.org/10.2352/issn.2169-4451.2002.18.1.art00048_1
Publikováno v:
NIP & Digital Fabrication Conference. 18:195-199
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbeffd7921a6530d52af0b801b60bc53
https://doi.org/10.2352/issn.2169-4451.2002.18.1.art00047_1
https://doi.org/10.2352/issn.2169-4451.2002.18.1.art00047_1
Publikováno v:
IEEE Transactions on Image Processing. 7:1029-1044
Markov random fields (MRF's) have been widely used to model images in Bayesian frameworks for image reconstruction and restoration. Typically, these MRF models have parameters that allow the prior model to be adjusted for best performance. However, o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c64e118541026f75710c55f09c100f0d
https://doi.org/10.1109/83.701163
https://doi.org/10.1109/83.701163
Publikováno v:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 9(10)
Bayesian tomographic reconstruction algorithms generally require the efficient optimization of a functional of many variables. In this setting, as well as in many other optimization tasks, functional substitution (FS) has been widely applied to simpl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60387d5d2b9d09fe8145c60d29dbaa6c
https://pubmed.ncbi.nlm.nih.gov/18262913
https://pubmed.ncbi.nlm.nih.gov/18262913
Publikováno v:
Computational Imaging
As printing proceeds in a thermal printer, heat from previously printed lines of image data accumulates in the print head and alters the thermal state of the heating elements. This fluctuating state of the heating elements manifests itself as a disto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ca84b6112022276fe3f6057f177e75c
https://doi.org/10.1117/12.586006
https://doi.org/10.1117/12.586006
Publikováno v:
Computational Imaging
The sharpness of a printed image may suffer due to the presence of material layers above and below the dye layers. These layers contribute to scattering and surface reflections that make the degradation in sharpness density-dependent. We present data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bdd4f5b8bb10c48f48f7463d6cd4fdd
https://doi.org/10.1117/12.586034
https://doi.org/10.1117/12.586034
Publikováno v:
ICASSP
A certain class of Markov random fields (MRF) known as generalized Gaussian MRFs (GGMRF) have been shown to yield good performance in modeling the a priori information in Bayesian image reconstruction and restoration problems. Though the ML estimate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cab0ffdd55ec25ea7abd4859f9c02b22
https://doi.org/10.1109/icassp.1996.545864
https://doi.org/10.1109/icassp.1996.545864
Publikováno v:
ICIP (2)
Statistical tomographic reconstruction algorithms generally require the efficient optimization of a functional. An algorithm known as iterative coordinate descent with Newton-Raphson updates (ICD/NR) has been shown to be much more computationally eff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26d766a97e087f424c304306da5dad2e
https://doi.org/10.1109/icip.1996.561002
https://doi.org/10.1109/icip.1996.561002
Publikováno v:
ICIP (2)
The popularity of Bayesian methods in image processing applications has generated great interest in image modeling. A good image model needs to be non-homogeneous to be able to adapt to the local characteristics of the different regions in an image.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4edb341943ce68c109a1663039d50c5f
https://doi.org/10.1109/icip.1996.560879
https://doi.org/10.1109/icip.1996.560879