K-SVD

An K-SVD implementaion written in Python.

Installation

pip install ksvd

Usage

import numpy as np
from ksvd import ApproximateKSVD


# X ~ gamma.dot(dictionary)
X = np.random.randn(1000, 20)
aksvd = ApproximateKSVD(n_components=128)
dictionary = aksvd.fit(X).components_
gamma = aksvd.transform(X)

Feature

• Approximate K-SVD

Example

• nel215/image-noise-reduction

License

Licensed under the Apache License 2.0.

References

• Rubinstein, R., Zibulevsky, M. and Elad, M., Efficient Implementation of the K-SVD Algorithm using Batch Orthogonal Matching Pursuit Technical Report - CS Technion, April 2008