منابع مشابه
Fundamental Limits of Blind Deconvolution Part I: Ambiguity Kernel
Blind deconvolution is an ubiquitous non-linear inverse problem in applications like wireless communications and image processing. This problem is generally ill-posed, and there have been efforts to use sparse models for regularizing blind deconvolution to promote signal identifiability. Part I of this two-part paper characterizes the ambiguity space of blind deconvolution and shows unidentifia...
متن کاملModel Regularization with Blind Deconvolution
Introduction: Dynamic contrast-enhanced MRI (DCE-MRI) is physiological imaging tool used clinically to aid the diagnosis and treatment monitoring of a variety of diseases. Pharmacokinetic parameters can be estimated by fitting DCE-MRI data to one of many mathematical models. The two-compartment model used here describes the concentration of contrast agent (CA) in tissue with respect to three pa...
متن کاملBlind Deconvolution with Sparse Priors on the Deconvolution Filters
In performing blind deconvolution to remove reverberation from speech signal, most acoustic deconvolution filters need a great many number of taps, and acoustic environments are often time-varying. Therefore, deconvolution filter coefficients should find their desired values with limited data, but conventional methods need lots of data to converge the coefficients. In this paper, we use sparse ...
متن کاملScale Factor Ambiguity Correction for Subband Blind Multichannel Identification
Subband system identification has proved beneficial in applications such as acoustic echo cancellation. A problem for blind multichannel system identification in subbands is that the subband systems can only be identified correctly up to an arbitrary scale factor. This scale factor ambiguity is the same across all channels but can differ between the subbands and therefore, limits the usability ...
متن کاملLight Field Blind Deconvolution
We address for the first time the issue of motion blur in light field images captured from plenoptic cameras (instead of camera arrays), where the spatial sampling in each view is decimated. We propose a solution to the estimation of a sharp light field given a blurry one, when the motion blur point spread function is unknown, i.e., the so-called blind deconvolution problem. Unfortunately, the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Sciences
سال: 2020
ISSN: 2076-3417
DOI: 10.3390/app10030939