Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Design of Efficient Regular Arrays for Matrix Multiplication by Two-Step Regularization
IEEE Transactions on Parallel and Distributed Systems
Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Independence: a new criterion for the analysis of the electromagnetic fields in the global brain?
Neural Networks - Special issue on the global brain: imaging and modelling
Parallel VLSI Neural System Design
Parallel VLSI Neural System Design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Dictionary learning algorithms for sparse representation
Neural Computation
Parallel Algorithm And Architecture For Two-Step Division-Free Gaussian Elimination
ASAP '96 Proceedings of the IEEE International Conference on Application-Specific Systems, Architectures, and Processors
Subset selection algorithms with applications
Subset selection algorithms with applications
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
A Variational Method for Learning Sparse and Overcomplete Representations
Neural Computation
Learning Overcomplete Representations
Neural Computation
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Sparse Bayesian learning for basis selection
IEEE Transactions on Signal Processing
An affine scaling methodology for best basis selection
IEEE Transactions on Signal Processing
Quadratic Gabor filters for object detection
IEEE Transactions on Image Processing
Special Issue On Representation And Coding Of Images And Video II
IEEE Transactions on Circuits and Systems for Video Technology
Algorithms for nonnegative independent component analysis
IEEE Transactions on Neural Networks
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
Neural Computation
Large-scale deep unsupervised learning using graphics processors
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Clustering-based denoising with locally learned dictionaries
IEEE Transactions on Image Processing
Hierarchical ALS algorithms for nonnegative matrix and 3D tensor factorization
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Image super-resolution via sparse representation
IEEE Transactions on Image Processing
Accelerating non-local denoising with a patch based dictionary
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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Images can be coded accurately using a sparse set of vectors from a learned overcomplete dictionary, with potential applications in image compression and feature selection for pattern recognition. We present a survey of algorithms that perform dictionary learning and sparse coding and make three contributions. First, we compare our overcomplete dictionary learning algorithm (FOCUSS-CNDL) with overcomplete independent component analysis (ICA). Second, noting that once a dictionary has been learned in a given domain the problem becomes one of choosing the vectors to form an accurate, sparse representation, we compare a recently developed algorithm (sparse Bayesian learning with adjustable variance Gaussians, SBL-AVG) to well known methods of subset selection: matching pursuit and FOCUSS. Third, noting that in some cases it may be necessary to find a non-negative sparse coding, we present a modified version of the FOCUSS algorithm that can find such non-negative codings. Efficient parallel implementations in VLSI could make these algorithms more practical for many applications.