Density driven diffusion

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In this work we derive a novel density driven diffusion scheme for image enhancement. Our approach, called D3, is a semi-local method that uses an initial structure-preserving oversegmentation step of the input image. Because of this, each segment will approximately conform to a homogeneous region in the image, allowing us to easily estimate parameters of the underlying stochastic process thus achieving adaptive non-linear filtering. Our method is capable of producing competitive results when compared to state-of-the-art methods such as non-local means, BM3D and tensor driven diffusion on both color and grayscale images. © 2013 Springer-Verlag.

Cite

CITATION STYLE

APA

Åström, F., Zografos, V., & Felsberg, M. (2013). Density driven diffusion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7944 LNCS, pp. 718–730). https://doi.org/10.1007/978-3-642-38886-6_67

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