A new method for multi-focus image fusion using Countourlet transform

Dempster-Shafer and Multi-Focus Image Fusion using Local Distance

10.5121/csit.2021.112206 ◽

2021 ◽

Author(s):

Ias Sri Wahyuni ◽

Rachid Sabre

Keyword(s):

Image Fusion ◽

Mass Function ◽

New Method ◽

Dempster Shafer Theory ◽

Local Distance ◽

Focus Image ◽

Fusion Images ◽

Shafer Theory ◽

Quadratic Distance ◽

Local Variability

In this article, we give a new method of multi-focus fusion images based on Dempster-Shafer theory using local variability (DST-LV). Indeed, the method takes into account the variability of observations of neighbouring pixels at the point studied. At each pixel, the method exploits the quadratic distance between the value of the pixel I (x, y) of the point studied and the value of all pixels which belong to its neighbourhood. Local variability is used to determine the mass function. In this work, two classes of Dempster-Shafer theory are considered: the fuzzy part and the focused part. We show that our method gives the significant and better result by comparing it to other methods.

Download Full-text

Multi-Focus Image Fusion Method via Multiple Wavelet Bases

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.467.604 ◽

2013 ◽

Vol 467 ◽

pp. 604-608

Author(s):

Wen Liu An ◽

Xiao Ling Wang

Keyword(s):

Image Fusion ◽

Weighted Average ◽

New Method ◽

Wavelet Bases ◽

Base Method ◽

Focus Image ◽

Fusion Images ◽

Local Gradient ◽

Image Fusion Method ◽

Better Than

In this article, a new method for multi-focus image fusion via multiple wavelet bases is proposed.Firstly the wavelet transform is used to perform a multiscale decomposion on each image , then based on local gradient in the fusion to get primary fusion image .And then a set of the primary fusion images are obtained.Next these primary fusion images are fused to obtain final fusion iamge within spatial domain based on local variances weighted average rule.Experimental results show the new method is better than the traditional single wavelet base method in fusion effect.

Download Full-text

Neighbour Local Variability for Multi-Focus Images Fusion

Signal & Image Processing An International Journal ◽

10.5121/sipij.2020.11603 ◽

2020 ◽

Vol 11 (6) ◽

pp. 37-51

Author(s):

Ias Sri Wahyuni ◽

Rachid Sabre

Keyword(s):

Image Fusion ◽

New Method ◽

Single Image ◽

Edge Function ◽

Focus Image ◽

Local Variability ◽

Region Size

The goal of multi-focus image fusion is to integrate images with different focus objects in order to obtain a single image with all focus objects. In this paper, we give a new method based on neighbour local variability (NLV) to fuse multi-focus images. At each pixel, the method uses the local variability calculated from the quadratic difference between the value of the pixel and the value of all pixels in its neighbourhood. It expresses the behaviour of the pixel with respect to its neighbours. The variability preserves the edge function because it detects the sharp intensity of the image. The proposed fusion of each pixel consists of weighting each pixel by the exponential of its local variability. The quality of this fusion depends on the size of the neighbourhood region considered. The size depends on the variance and the size of the blur filter. We start by modelling the value of the neighbourhood region size as a function of the variance and the size of the blur filter. We compare our method to other methods given in the literature. We show that our method gives a better result.

Download Full-text