H. Lantéri
University of Nice Sophia Antipolis
37 Papers
141 Citations
H. Lantéri is an academic researcher from University of Nice Sophia Antipolis. The author has contributed to research in topics: Deconvolution & Iterative method. The author has an hindex of 11, co-authored 36 publications.
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Papers
Comparison between isra and rla algorithms. use of a wiener filter based stopping criterion
TL;DR: In this paper, the authors compare Richardson-Lucy (RLA) and Image Space Reconstruction Algorithm (ISRA) for image deconvolu- tion of astronomical images, and propose a new objective stopping technique that makes use of a com- parison of the results of these algorithms with that of the Wiener lter.
First results of the PML monitor of atmospheric turbulence profile with high vertical resolution
Aziz Ziad,Flavien Blary,Julien Borgnino,Y. Fantei-Caujolle,Eric Aristidi,F. Martin,H. Lantéri,R. Douet,E. Bondoux,D. Mekarnia +9 more
TL;DR: In this article, a new monitor called Profiler of Moon Limb (PML) is presented for the extraction of the C 2 N (h) profile with high vertical resolution and its first results are presented.
Linear unmixing of hyperspectral images using a scaled gradient method
Celine Theys,Nicolas Dobigeon,Jean-Yves Tourneret,H. Lantéri +3 more
- 06 Oct 2009
TL;DR: In this paper, two scaled gradient iterative methods are proposed for estimating the abundances of the linear mixing model, including a normalization step in the scaled gradient method and the sum-to-one constraint in the observation model with an appropriate weighting parameter.
Ringing reduction in image restoration algorithms using a constraint on the inferior bound of the solution
TL;DR: A general method allowing to devise maximum-likelihood image restoration algorithms with a general constraint on the inferior bound of the solution, this bound can be different at each point of the signal; ringing phenomena are then reduced.
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Application of the Richardson-Lucy algorithm to the deconvolution of two-fold probability density functions
TL;DR: In this article, the Richardson-Lucy algorithm is used to deconvolve a set of images which are grey level representations of slices of two-fold probability density functions (PDFs) computed from the one-dimensional signal obtained with the ESO slit scanning infrared specklograph.
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