Title :

Using saliency detection to improve multi-focus image fusion

Author(s) :

Babahenini, Sarra [Auteur]
Charif, Fella [Auteur]
Cherif, Foudil [Auteur]
Taleb-Ahmed, Abdelmalik [Auteur]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Ruichek, Yassine [Auteur]
Connaissance et Intelligence Artificielle Distribuées [Dijon] [CIAD]

Journal title :

International Journal of Signal and Imaging Systems Engineering

Pages :

81 - 92

Publisher :

Inderscience

Publication date :

2021-10-04

ISSN :

1748-0698

English keyword(s) :

human vision system
visual saliency detection
saliency map
multi-focus
image fusion
weight map
contourlet transform
matrix decomposition.

HAL domain(s) :

Sciences de l'ingénieur [physics]

English abstract : [en]

In this paper, we introduce a novel and efficient algorithm based on saliency detection methods, our main contribution is a new manner to calculate the weight map by normalising the saliency values obtained from the input ...
Show more >In this paper, we introduce a novel and efficient algorithm based on saliency detection methods, our main contribution is a new manner to calculate the weight map by normalising the saliency values obtained from the input images, which makes it possible to differentiate the focused and defocused regions. We have experiment three techniques of computing the weight map using contourlet transform and low-rank and structured sparse matrix decomposition (LSMD) model. The performance of the proposed model is compared with that of the state-of-the-art multi-focus fusion methods by using fusion metrics. Our evaluation of a series of dataset image demonstrate that the proposed method provides an improvement both visual quality and objective assessment compared to existing methods.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL