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. The purpose of the book is to provide a comprehensive account of the theoretical results, methods and algorithms related to the problem of image reconstruction from Poisson data within the framework of the maximum likelihood approach introduced by Shepp and Vardi
The Poisson distribution arises naturally when dealing with data involving counts, and it has found ...
Recently, Poisson noise has become of great interest in many imaging applications. When regularizati...
Poisson noise models arise in a wide range of linear inverse problems in imaging. In the Bayesian se...
The application of Poisson data inversions is important in both specific and very different domains ...
Abstract. In image processing applications, image intensity is often measured via the counting of in...
Abstract—Poisson inverse problems arise in many modern imaging applications, including biomedical an...
Journal PaperThis paper describes a statistical modeling and analysis method for linear inverse prob...
Inverse problems with Poisson data arise in many photonic imaging modalities in medicine, engineerin...
Abstract. Poisson noise models arise in a wide range of linear inverse problems in imaging. In the B...
In many imaging applications the image intensity is measured by counting incident particles and, con...
International audienceWe consider the reconstruction of an image from a sequence of a few linear mea...
In applications of imaging science, such as emissiontomography, fluorescence microscopy and optical/...
Abstract—The observations in many applications consist of counts of discrete events, such as photons...
Founding on a physical transformation process described by a Fredholm integral equation of the first...
International audienceMany biomedical imaging techniques, such as computerized tomography, positron ...
The Poisson distribution arises naturally when dealing with data involving counts, and it has found ...
Recently, Poisson noise has become of great interest in many imaging applications. When regularizati...
Poisson noise models arise in a wide range of linear inverse problems in imaging. In the Bayesian se...
The application of Poisson data inversions is important in both specific and very different domains ...
Abstract. In image processing applications, image intensity is often measured via the counting of in...
Abstract—Poisson inverse problems arise in many modern imaging applications, including biomedical an...
Journal PaperThis paper describes a statistical modeling and analysis method for linear inverse prob...
Inverse problems with Poisson data arise in many photonic imaging modalities in medicine, engineerin...
Abstract. Poisson noise models arise in a wide range of linear inverse problems in imaging. In the B...
In many imaging applications the image intensity is measured by counting incident particles and, con...
International audienceWe consider the reconstruction of an image from a sequence of a few linear mea...
In applications of imaging science, such as emissiontomography, fluorescence microscopy and optical/...
Abstract—The observations in many applications consist of counts of discrete events, such as photons...
Founding on a physical transformation process described by a Fredholm integral equation of the first...
International audienceMany biomedical imaging techniques, such as computerized tomography, positron ...
The Poisson distribution arises naturally when dealing with data involving counts, and it has found ...
Recently, Poisson noise has become of great interest in many imaging applications. When regularizati...
Poisson noise models arise in a wide range of linear inverse problems in imaging. In the Bayesian se...