Separation of reflection components by sparse non-negative matrix factorization

Separation of Reflection Components by Sparse Non-negative Matrix Factorization

This paper presents a novel method for separating reflection components in a single image based on the dichromatic reflection model. Our method is based on a modified version of sparse non-negative matrix factorization (NMF). It simultaneously performs the estimation of body colors and the separation of reflection components through optimization. Our method does not use a spatial prior such as ...

Single-channel speech separation using sparse non-negative matrix factorization

We apply machine learning techniques to the problem of separating multiple speech sources from a single microphone recording. The method of choice is a sparse non-negative matrix factorization algorithm, which in an unsupervised manner can learn sparse representations of the data. This is applied to the learning of personalized dictionaries from a speech corpus, which in turn are used to separa...

Speech Separation using Non-negative Features and Sparse Non-negative Matrix Factorization

This paper describes a method for separating two speakers in a single channel recording. The separation is performed in a low dimensional feature space optimized to represent speech. For each speaker, an overcomplete basis is estimated using sparse non-negative matrix factorization, and a mixture is separated by mapping the mixture onto the joint bases of the two speakers. The method is evaluat...

Sparse Non-negative Matrix Factorization and its Application in Overlapped Chromatograms Separation

A new NMF algorithm has been proposed for the deconvolution of overlapping chromatograms of chemical mixture. Most of the NMF algorithms used so far for chromatogram separation do not converge to a stable limit point. To get same results for all the runs, instead of random initialization, three different initialization methods have been used namely, ALS-NMF (robust initialization), NNDSVD based...

Non-negative matrix factorization