Denoising an image by denoising its components in a moving frame

4Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this paper, we provide a new non-local method for image denoising. The key idea we develop is to denoise the components of the image in a well-chosen moving frame instead of the image itself. We prove the relevance of our approach by showing that the PSNR of a grayscale noisy image is lower than the PSNR of its components. Experiments show that applying the Non Local Means algorithm of Buades et al. [5] on the components provides better results than applying it directly on the image. © 2014 Springer International Publishing.

Cite

CITATION STYLE

APA

Ghimpe, G., Batard, T., Bertalmío, M., & Levine, S. (2014). Denoising an image by denoising its components in a moving frame. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8509 LNCS, pp. 375–383). Springer Verlag. https://doi.org/10.1007/978-3-319-07998-1_43

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free