Open Access Open Access  Restricted Access Subscription or Fee Access

An improved Smoothing Method Based on Diffusion Equation and K-means Clustering

Ouhda Mohamed, Ouanan Mohammed, Aksasse Brahim


When an image is acquired by a camera or other imaging system, the vision system for which it is intended is often unable to directly use it. The image may be corrupted because of random variations in intensity, variations in illumination, or poor contrast that must be dealt with in the early stages of vision processing. The main goal of this paper is to discuss partial differential equation methods for image enhancement aimed at eliminating these undesirable characteristics. We propose a improved filtering method, based on diffusion equation and k-means segmentation. The experimental results show that the proposed method has a better smoothing performance compared with the Perona-Malik method that uses the anisotropic diffusion. In addition, the proposed approach is simple and can provide a better smoothing in a few iterations, which gives, in a short execution time, a better image filtering.

Full Text:



  • There are currently no refbacks.

Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.