Title
Blind Restoration Of Confocal Microscopy Images In Presence Of A Depth-Variant Blur And Poisson Noise
Abstract
We are interested in blind image restoration in confocal laser scanning microscopy (CLSM). Two challenging problems in this imaging system are considered: First, spherical aberrations due to refractive index mismatch leads to a depth variant (DV) blur. Second, low illumination leads to a signal dependent Poisson noise. In addition, the DV point spread function (PSF) is unknown, which increases the complexity of the problem considered. Our goal is to remove in a blind framework both the DV blur and the Poisson noise from CLSM images. Using an approximation of the DV PSF, we define in a Bayesian framework a criterion to be jointly minimized w. r. t. the specimen function and the PSF. We then adopt an alternate minimization scheme for the optimization problem. For each elementary minimization, we use the recently proposed scaled gradient projection (SGP) algorithm that has shown a fast convergence rate. Results are shown on simulated and real CLSM images.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6637782
2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Blind restoration, confocal microscopy, depth-variant PSF, JMAP, SGP algorithm
Computer vision,Optical transfer function,Computer science,Minimisation (psychology),Artificial intelligence,Rate of convergence,Image restoration,Poisson distribution,Point spread function,Shot noise,Optimization problem
Conference
ISSN
Citations 
PageRank 
1520-6149
7
0.48
References 
Authors
8
4
Name
Order
Citations
PageRank
Saima Ben Hadj1111.29
Laure Blanc-Féraud253663.97
Gilles Aubert31275108.17
Gilbert Engler481.21