Depth variant image restoration in 3D fluorescence microscopy: two approaches under Gaussian and Poissonian noise conditions

Saima Ben Hadj 1 Laure Blanc-Féraud 1 Elie Maalouf 2 Bruno Colicchio 2 Alain Dieterlen 2
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : In this article, we are interested in restoring images from 3D fluorescence microscopy. In fact, these images are affected by a depth-variant blur due to light refraction phenomenon. We present and compare two different restoration strategies for that problem. The first one is based on multiple deconvolutions with depth-invariant blur functions and the second one consists in using a depth-variant blur function in the deconvolution process. Furthermore, we fit two deconvolution algorithms to this problem. First, we use the Richardson-Lucy method with total variation regularization to restore confocal microscopy images which are affected by a Poisson noise. Then, we focus on restoring wide field microscopy images which are corrupted by a Gaussian noise. Tests on simulated data show that the second restoration strategy is slightly more accurate than the first one for both noise conditions.
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Conference papers
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https://hal.inria.fr/hal-00765002
Contributor : Laure Blanc-Féraud <>
Submitted on : Thursday, December 13, 2012 - 10:51:40 PM
Last modification on : Monday, November 5, 2018 - 3:52:02 PM

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Saima Ben Hadj, Laure Blanc-Féraud, Elie Maalouf, Bruno Colicchio, Alain Dieterlen. Depth variant image restoration in 3D fluorescence microscopy: two approaches under Gaussian and Poissonian noise conditions. ISBI 2012 - 9th International Symposium on Biomedical Imaging, May 2012, Barcelona, Spain. pp.1671-1674, ⟨10.1109/ISBI.2012.6235899⟩. ⟨hal-00765002⟩

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