scholarly journals Fast & Robust Image Interpolation Using Gradient Graph Laplacian Regularizer

2021 ◽  
Author(s):  
Fei Chen ◽  
Gene Cheung ◽  
Xue Zhang
Keyword(s):  
Image Interpolation ◽  
Graph Laplacian ◽  
Robust Image

Multiresolution Bio-Medical Image Segmentation using Fuzzy C-Means Clustering

2019 ◽  
Vol 8 (4) ◽  
pp. 9548-9551
Keyword(s):  
Image Segmentation ◽  
Medical Image Segmentation ◽  
Experimental Result ◽  
Segmentation Method ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Robust Image ◽  
Multiple Clusters ◽  
Single Pixel ◽  
Popular Image

Fuzzy c-means clustering is a popular image segmentation technique, in which a single pixel belongs to multiple clusters, with varying degree of membership. The main drawback of this method is it sensitive to noise. This method can be improved by incorporating multiresolution stationary wavelet analysis. In this paper we develop a robust image segmentation method using Fuzzy c-means clustering and wavelet transform. The experimental result shows that the proposed method is more accurate than the Fuzzy c-means clustering.

Mathematics of networks

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Random Walks ◽  
Adjacency Matrix ◽  
Graph Partitioning ◽  
Dynamic Networks ◽  
Graph Laplacian ◽  
Network Visualization ◽  
Final Part ◽  
Bipartite Networks ◽  
Component Structure ◽  
Basic Properties

An introduction to the mathematical tools used in the study of networks. Topics discussed include: the adjacency matrix; weighted, directed, acyclic, and bipartite networks; multilayer and dynamic networks; trees; planar networks. Some basic properties of networks are then discussed, including degrees, density and sparsity, paths on networks, component structure, and connectivity and cut sets. The final part of the chapter focuses on the graph Laplacian and its applications to network visualization, graph partitioning, the theory of random walks, and other problems.

scholarly journals Spectral Gap of the Largest Eigenvalue of the Normalized Graph Laplacian

2021 ◽  
Author(s):  
Jürgen Jost ◽  
Raffaella Mulas ◽  
Florentin Münch
Keyword(s):  
Lower Bound ◽  
Bipartite Graph ◽  
Spectral Gap ◽  
Complete Bipartite Graph ◽  
Graph Laplacian ◽  
New Method ◽  
Single Edge ◽  
Largest Eigenvalue ◽  
Complement Graph ◽  
The Largest Eigenvalue

AbstractWe offer a new method for proving that the maxima eigenvalue of the normalized graph Laplacian of a graph with n vertices is at least $$\frac{n+1}{n-1}$$ n + 1 n - 1 provided the graph is not complete and that equality is attained if and only if the complement graph is a single edge or a complete bipartite graph with both parts of size $$\frac{n-1}{2}$$ n - 1 2 . With the same method, we also prove a new lower bound to the largest eigenvalue in terms of the minimum vertex degree, provided this is at most $$\frac{n-1}{2}$$ n - 1 2 .

scholarly journals Active Contour Model with Adaptive weighted function for Robust Image Segmentation under Biased Conditions

2021 ◽  
pp. 114811
Author(s):  
Aditi Joshi ◽  
Mohammed Saquib Khan ◽  
Asim Niaz ◽  
Farhan Akram ◽  
Hyun Chul Song ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Active Contour Model ◽  
Weighted Function ◽  
Contour Model ◽  
Robust Image

scholarly journals Low-Cost Implementation of Bilinear and Bicubic Image Interpolation for Real-Time Image Super-Resolution

2020 ◽  
Author(s):  
Donya Khaledyan ◽  
Abdolah Amirany ◽  
Kian Jafari ◽  
Mohammad Hossein Moaiyeri ◽  
Abolfazl Zargari Khuzani ◽  
...  
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Super Resolution ◽  
Image Interpolation ◽  
Real Time Image ◽  
Image Super Resolution ◽  
Time Image
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