Paper Info
Title
Denoising based Vector Approximate Message Passing.
Abstract
The denoising-based approximate message passing (D-AMP) methodology, recently proposed by Metzler, Maleki, and Baraniuk, allows one to plug in sophisticated denoisers like BM3D into the AMP algorithm to achieve state-of-the-art compressive image recovery. But AMP diverges with small deviations from the i.i.d.-Gaussian assumption on the measurement matrix. Recently, the vector AMP (VAMP) algorithm has been proposed to fix this problem. In this work, we show that the benefits of VAMP extend to D-VAMP.
Year
Venue
Field
2016
arXiv: Information Theory
Noise reduction,Mathematical optimization,Matrix (mathematics),Computer science,Algorithm,Theoretical computer science,Plug-in,Image recovery,Message passing
DocType
Volume
Citations 
Journal
abs/1611.01376
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Philip Schniter1162093.74
Sundeep Rangan23101163.90
Alyson K. Fletcher355241.10