loading
Dictionary-based reconstruction of the cyclic autocorrelation via 1 -minimization for cyclostationary spectrum sensing
2013 Edition, May 1, 2013 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

One of the main enablers of dynamic spectrum access is fast and reliable spectrum sensing. Acquiring the occupation status of a spectral band can be accomplished in different ways, one of which is called cyclostationary...

Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging
2013 Edition, Volume 32, November 1, 2013 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the...

Dictionary based reconstruction and classification of randomly sampled sensor network data
2012 Edition, June 1, 2012 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this paper, we propose a method for recovering and classifying WSN data while minimizing the number of samples that need to be acquired, processed, and transmitted. The problem is formulated according to the recently proposed framework of Matrix...

An over-complete dictionary based regularized reconstruction of a field of ensemble average propagators
2012 Edition, May 1, 2012 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this paper we present a dictionary-based framework for the reconstruction of a field of ensemble average propagators (EAPs), given a high angular resolution diffusion MRI data set. Existing techniques often consider voxel-wise...

Dictionary learning based panel PET image reconstruction
2014 Edition, November 1, 2014 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In our previous work, we have proposed a stationary panel positron emission tomography (PET) for human body imaging. Besides the large solid angle, the panel PET also provides an open geometry which allows other operations being performed simultaneously during a PET scanning....

Physics-driven deep training of dictionary-based algorithms for MR image reconstruction
2017 Edition, October 1, 2017 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Techniques involving learned dictionaries can outperform conventional approaches involving (nontrained) analytical sparsifying models for MR image reconstruction. Inspired by iterative dictionary learning-based reconstruction methods, we propose a novel...

Dual-dictionary learning based MR image reconstruction with self-adaptive dictionaries
2015 Edition, August 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Dual-dictionary learning method utilizes two dictionaries at two different resolution levels, a high resolution dictionary trained with full-data training set, and a low resolution dictionary co-trained with corresponding undersampled dataset. This method effectively...

Tensor-Based Dictionary Learning for Spectral CT Reconstruction
2017 Edition, Volume 36, January 1, 2017 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among...

Complexity reduction in multi-dictionary based single-image superresolution reconstruction via pahse congtuency
2015 Edition, July 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Compared with single dictionary, multi-dictionary method can achieve better performance in image superresolution reconstruction (SR). However, the computational cost of multi-dictionary based SR is very heavy and usually time-consuming and...

Dictionary learning-based approach for SAR image reconstruction
2014 Edition, April 1, 2014 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Recently there has been growing interest on the study of sparse representation-based SAR imaging with the assumption that the underlying SAR scenes exhibit sparsity with respect to SAR image features such as point scatterers and edges of smooth regions....

Advertisement