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

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.

Multi-Focus Image Fusion Method via Multiple Wavelet Bases

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.

scholarly journals Neighbour Local Variability for Multi-Focus Images Fusion

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.

A new method based on Dempster–Shafer theory and fuzzy c-means for brain MRI segmentation

2015 ◽  
Vol 26 (10) ◽  
pp. 105402 ◽  
Author(s):  
Jie Liu ◽  
Xi Lu ◽  
Yunpeng Li ◽  
Xiaowu Chen ◽  
Yong Deng
Keyword(s):  
Brain Mri ◽  
New Method ◽  
Mri Segmentation ◽  
Fuzzy C Means ◽  
Dempster Shafer Theory ◽  
Shafer Theory

Information-Based Evaluation of Approximation Methods in Dempster-Shafer Theory

2016 ◽  
Vol 24 (04) ◽  
pp. 503-535 ◽  
Author(s):  
Atiye Sarabi-Jamab ◽  
Babak N. Araabi
Keyword(s):  
Approximation Algorithms ◽  
Approximation Method ◽  
Mass Function ◽  
Evaluation Methodology ◽  
Computational Time ◽  
Approximation Methods ◽  
Dempster Shafer Theory ◽  
New Information ◽  
Qualitative Performance ◽  
Shafer Theory

Complexity of computations, particularly due to large number of focal elements (FEs), in Dempster-Shafer theory (DST) motivates the development of approximation algorithms. Existing approximation methods include efficient algorithm for special hypothesis space, Monte Carlo based techniques, and simplification procedures. In this paper, the quality of the simplification-based approximation algorithms is evaluated using a new information-based comparison methodology. To this end, three structured testbeds are introduced. Each testbed is designed with an eye on a particular form of uncertainty associated with a body of evidence (BoE) in DST, i.e., conflict and non-specificity. Three proposed testbeds along with the classic testbed are utilized to evaluate the accuracy and complexity of existing algorithms. In light of the proposed evaluation methodology, a new approximation method is presented as well. The proposed algorithm has the ability to choose the most informative FEs without being forced to select the FEs with the largest mass function. Comparison of overall qualitative performance of approximation algorithms provides accuracy versus computational time tradeoff to choose an appropriate approximation method in different applications. Moreover, experiments with testbeds indicate that our proposed algorithm enhances the accuracy and computational tractability simultaneously.

scholarly journals A Signature Analysis Method for IC Failure Analysis

1996 ◽  
Author(s):  
C.L. Henderson ◽  
J.M. Soden
Keyword(s):  
Failure Analysis ◽  
Failure Mechanism ◽  
Experiential Knowledge ◽  
New Method ◽  
Signature Analysis ◽  
Analysis Method ◽  
Dempster Shafer Theory ◽  
Shafer Theory

Abstract A new method of signature analysis is presented and explained. This method of signature analysis can be based on either experiential knowledge of failure analysis, observed data, or a combination of both. The method can also be used on low numbers of failures or even single failures. It uses the Dempster-Shafer theory to calculate failure mechanism confidence. The model is developed in the paper and an example is given for its use.

Research and Application of the Improved DST New Method Based on Fuzzy Consistent Matrix and the Weighted Average

2014 ◽  
Vol 1030-1032 ◽  
pp. 1764-1768 ◽  
Author(s):  
Wei Xiao Xu ◽  
Ji Wen Tan ◽  
Hong Zhan
Keyword(s):  
Fault Diagnosis ◽  
Evidence Synthesis ◽  
Weighted Average ◽  
Rolling Bearing ◽  
New Method ◽  
Cnc Machine ◽  
Bearing Fault Diagnosis ◽  
Dempster Shafer Theory ◽  
High Conflict ◽  
Shafer Theory

Aiming at the existing defects of evidence dempster-shafer theory (DST) in dealing with high conflict evidence, we proposed a new method to improve DST. By introducing concept of fuzzy consistent matrix, calculate the weights of factors, and put different sources of evidence into distinguish, and finally cast more than one vote to prevent the phenomenon, the average convergence of evidence. What’s more, the improved DST new method is applied to the rolling bearing fault diagnosis of CNC machine workbench .The test results show that the improved new synthetic formula increases the accuracy of fault diagnosis Ball, the conflict of evidence synthesis results better, to achieve better results.

A new method to rank fuzzy numbers using Dempster–Shafer theory with fuzzy targets

2016 ◽  
Vol 346-347 ◽  
pp. 302-317 ◽  
Author(s):  
Kok Chin Chai ◽  
Kai Meng Tay ◽  
Chee Peng Lim
Keyword(s):  
Fuzzy Numbers ◽  
New Method ◽  
Dempster Shafer Theory ◽  
Shafer Theory

Sensitivity Analysis of Epistemic Uncertainty on Input Parameters and System Structure Using Dempster-Shafer Theory

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Yunhui Hou
Keyword(s):  
Sensitivity Analysis ◽  
System Reliability ◽  
Early Stage ◽  
Epistemic Uncertainty ◽  
Mass Function ◽  
System Structure ◽  
System Level ◽  
Numerical Application ◽  
Dempster Shafer Theory ◽  
Shafer Theory

Abstract In this article, a method is proposed to conduct a global sensitivity analysis of epistemic uncertainty on both system input and system structure, which is very common in early stage of system development, using Dempster-Shafer theory (DST). In system reliability assessment, the input corresponds to component reliability and system structure is given by system reliability function, cut sets, or truth table. A method to propagate real-number mass function through set-valued mappings is introduced and applied on system reliability calculation. Secondly, we propose a method to model uncertain system with multiple possible structures and how to obtain the mass function of system level reliability. Finally, we propose an indicator for global sensibility analysis. Our method is illustrated, and its efficacy is proved by numerical application on two case studies.

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