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Conference Papers Year : 2012

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

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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Dates and versions

hal-00765002 , version 1 (13-12-2012)

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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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