Constrained Restoration and the Recovery of Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Concept decompositions for large sparse text data using clustering
Machine Learning
Dictionary learning algorithms for sparse representation
Neural Computation
Introducing a weighted non-negative matrix factorization for image classification
Pattern Recognition Letters
Non-negative matrix factorization based methods for object recognition
Pattern Recognition Letters
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
Nonnegative features of spectro-temporal sounds for classification
Pattern Recognition Letters
Nonsmooth Nonnegative Matrix Factorization (nsNMF)
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Generalized Divergence Measure for Nonnegative Matrix Factorization
Neural Computation
Learning Image Components for Object Recognition
The Journal of Machine Learning Research
Fast nonnegative matrix factorization and its application for protein fold recognition
EURASIP Journal on Applied Signal Processing
Regularized Alternating Least Squares Algorithms for Non-negative Matrix/Tensor Factorization
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Document clustering using nonnegative matrix factorization
Information Processing and Management: an International Journal
Csiszár’s divergences for non-negative matrix factorization: family of new algorithms
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Nonnegative Tensor Factorization with Smoothness Constraints
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
NOLISP'11 Proceedings of the 5th international conference on Advances in nonlinear speech processing
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Nonnegative Matrix Factorization (NMF) has already found many applications in image processing and data analysis, including classification, clustering, feature extraction, pattern recognition, and blind image separation. In the paper, we extend the selected NMF algorithms by taking into account local smoothness properties of source images. Our modifications are related with incorporation of the Gibbs prior, which is well-known in many tomographic image reconstruction applications, to a underlying blind image separation model. The numerical results demonstrate the improved performance of the proposed methods in comparison to the standard NMF algorithms.