Spatial PCA as a new method for image fusion

Author(s):  
Hamid Reza Shahdoosti ◽  
Hassan Ghassemian
Keyword(s):  
2021 ◽  
Author(s):  
Ias Sri Wahyuni ◽  
Rachid Sabre

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.


2013 ◽  
Vol 467 ◽  
pp. 604-608
Author(s):  
Wen Liu An ◽  
Xiao Ling Wang

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.


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