Multilevel algorithm for a Poisson noise removal model with total-variation regularization
International Journal of Computer Mathematics - Fast Iterative and Preconditioning Methods for Linear and Non-Linear Systems
Bregman-EM-TV Methods with Application to Optical Nanoscopy
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
A proximal iteration for deconvolving Poisson noisy images using sparse representations
IEEE Transactions on Image Processing
Performance bounds on compressed sensing with Poisson noise
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Deblurring Poissonian images by split Bregman techniques
Journal of Visual Communication and Image Representation
Compressed sensing performance bounds under Poisson noise
IEEE Transactions on Signal Processing
Restoration of Poissonian images using alternating direction optimization
IEEE Transactions on Image Processing
A statistical multiscale framework for Poisson inverse problems
IEEE Transactions on Information Theory
Decoding by linear programming
IEEE Transactions on Information Theory
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
IEEE Transactions on Information Theory
This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice
IEEE Transactions on Image Processing
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In this paper, we consider 3D Bioluminescence tomography (BLT) source reconstruction from Poisson data in three dimensional space. With a priori information of sources sparsity and MAP estimation of Poisson distribution, we study the minimization of Kullback-Leihbler divergence with 驴 1 and 驴 0 regularization. We show numerically that although several 驴 1 minimization algorithms are efficient for compressive sensing, they fail for BLT reconstruction due to the high coherence of the measurement matrix columns and high nonlinearity of Poisson fitting term. Instead, we propose a novel greedy algorithm for 驴 0 regularization to reconstruct sparse solutions for BLT problem. Numerical experiments on synthetic data obtained by the finite element methods and Monte-Carlo methods show the accuracy and efficiency of the proposed method.