Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Nico Persch"'
Publikováno v:
Image and Vision Computing. 57:114-129
We propose a novel variational approach to the depth-from-defocus problem. The quality of such methods strongly depends on the modelling of the image formation (forward operator) that connects depth with out-of-focus blur. Therefore, we discuss diffe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88424698b6c2a0143f40e680c9cda183
https://doi.org/10.1016/j.imavis.2016.08.011
https://doi.org/10.1016/j.imavis.2016.08.011
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319117515
GCPR
GCPR
Given an image stack that captures a static scene with different focus settings, variational depth–from–defocus methods aim at jointly estimating the underlying depth map and the sharp image. We show how one can improve existing approaches by inc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eca7571dab34e455564c8d396976786e
https://doi.org/10.1007/978-3-319-11752-2_2
https://doi.org/10.1007/978-3-319-11752-2_2
Autor:
Martin Welk, Annette Kraegeloh, Andrés Bruhn, Sven Grewenig, Joachim Weickert, Ahmed Elhayek, Nico Persch, Katharina Böse
Publikováno v:
Measurement Science and Technology. 24:125703
This paper proposes an advanced image enhancement method that is specifically tailored towards 3-D confocal and STED microscopy imagery. Our approach unifies image denoising, deblurring and interpolation in one joint method to handle the typical weak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd12346348564ef575e01945672bb15b
https://doi.org/10.1088/0957-0233/24/12/125703
https://doi.org/10.1088/0957-0233/24/12/125703