Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering

Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering Publisher

Niknejad M¹ ; Rabbani H² ; Babaiezadeh M³ ; Jutten C⁴

Show Affiliations

1. Islamic Azad University, Majlesi Branch, Iran
2. Department of Biomedical Engineering, Isfahan University of Medical Sciences, Iran
3. Sharif University of Technology, Department of Electrical Engineering, Tehran, Iran
4. GIPSA-lab, Grenoble and Institut Universitaire de France, France

Source: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings Published:2015

Abstract

In this paper we address the problem of image interpolation using Gaussian Mixture Models (GMM) as a prior. Previous methods of image restoration with GMM have not considered spatial (geometric) distance between patches in clustering, failing to fully exploit the coherency of nearby patches. The GMM framework in our method for image interpolation is based on the assumption that the accumulation of similar patches in a neighborhood are derived from a multivariate Gaussian probability distribution with a specific covariance and mean. An Expectation Maximization-like (EM-like) algorithm is used in order to determine patches in a cluster and restore them. The results show that our image interpolation method outperforms previous state-of-the-art methods with an acceptable bound. © 2015 IEEE.

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Style	Citing Format
MLA	Niknejad M, et al.. "Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering." ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2015-August, no. , 2015, pp. 1613-1617.
APA	Niknejad M, Rabbani H, Babaiezadeh M, Jutten C (2015). Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2015-August(), 1613-1617.
Chicago	Niknejad M, Rabbani H, Babaiezadeh M, Jutten C. "Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering." ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 2015-August, no. (2015): 1613-1617.
Harvard	Niknejad M et al. (2015) 'Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering', ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2015-August(), pp. 1613-1617.
Vancouver	Niknejad M, Rabbani H, Babaiezadeh M, Jutten C. Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2015;2015-August():1613-1617.
BibTex	@article{ author = {Niknejad M and Rabbani H and Babaiezadeh M and Jutten C}, title = {Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering}, journal = {ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings}, volume = {2015-August}, number = {}, pages = {1613-1617}, year = {2015} }
RIS	TY - JOUR AU - Niknejad M AU - Rabbani H AU - Babaiezadeh M AU - Jutten C TI - Image Interpolation Using Gaussian Mixture Models With Spatially Constrained Patch Clustering JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings VL - 2015-August IS - SP - 1613 EP - 1617 PY - 2015 ER -

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