TY  - BOOK
AU  - Bertero,Mario
AU  - Boccacci,Patrizia
AU  - Ruggiero,Valeria
ED  - Institute of Physics (Great Britain),
TI  - Inverse imaging with Poisson data: from cells to galaxies 
T2  - [IOP release 6]
SN  - 9780750314374
AV  - TA1637 .B475 2018eb
U1  - 621.36/7/0151535 23
PY  - 2018///]
CY  - Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK)
PB  - IOP Publishing
KW  - Image processing
KW  - Mathematics
KW  - Inverse problems (Differential equations)
KW  - Poisson distribution
KW  - Imaging systems & technology
KW  - bicssc
KW  - TECHNOLOGY & ENGINEERING / Imaging Systems
KW  - bisacsh
N1  - "Version: 20181201"--Title page verso; Includes bibliographical references; 1. Introduction -- 1.1. Scope of the book and topic selection -- 1.2. Structure of the book; 2. Examples of applications -- 2.1. Fluorescence microscopy -- 2.2. Medical imaging (tomography) -- 2.3. Astronomy; 3. Mathematical modeling -- 3.1. Imaging system and forward problem -- 3.2. Ill-posedness of the backward (inverse) problem -- 3.3. Detection and data sampling -- 3.4. Detection and data noise -- 3.5. The discrete models -- 3.6. Supplementary ma; 4. Statistical approaches in a discrete setting -- 4.1. Maximum likelihood approach and data-fidelity function -- 4.2. Bayesian regularization -- 4.3. Denoising problems -- 4.4. Selection of the regularization parameter -- 4.5. The Bregman itera; 5. Simple reconstruction methods -- 5.1. Expectation maximization (EM) or Richardson-Lucy (RL) method -- 5.2. Ordered subset expectation maximization method -- 5.3. One-step late (OSL) method -- 5.4. Split gradient method (SGM) -- 5.5. Supplemen; 6. Optimization methods -- 6.1. Some basic tools : proximity operators and conjugate functions -- 6.2. The family of forward-backward (FB) splitting methods -- 6.3. FB methods for smooth problems of image reconstruction -- 6.4. FB methods for no; 7. Numerics -- 7.1. Semi-convergent methods -- 7.2. Methods for edge-preserving regularization -- 7.3. Image reconstruction of real data; 8. Specific topics in image deblurring -- 8.1. Super-resolution by data inversion -- 8.2. Boundary artifacts correction -- 8.3. Blind deconvolution -- 8.4. Images with point and smooth sources -- 8.5. Images with space-variant blur; 9. Towards a regularization theory -- 9.1. Deterministic regularization approaches -- 9.2. Statistical approaches -- 9.3. Comments and concluding remarks; Also available in print
N2  - Inverse Imaging with Poisson Data is an invaluable resource for graduate students, postdocs and researchers interested in the application of inverse problems to the domains of applied sciences, such as microscopy, medical imaging and astronomy.
UR  - https://ezproxy.mef.edu.tr/login?url=https://iopscience.iop.org/book/978-0-7503-1437-4
ER  -