Journal ArticleDOI
Infrared and visible images fusion based on RPCA and NSCT
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TLDR
Experimental results demonstrate that the proposed new infrared and visible image fusion algorithm can highlight the infrared objects as well as retain the background information in visible image.About:
This article is published in Infrared Physics & Technology.The article was published on 2016-07-01. It has received 66 citations till now. The article focuses on the topics: Contourlet.read more
Citations
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Infrared and visible image fusion methods and applications: A survey
TL;DR: This survey comprehensively survey the existing methods and applications for the fusion of infrared and visible images, which can serve as a reference for researchers inrared and visible image fusion and related fields.
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A survey of infrared and visual image fusion methods
TL;DR: It is concluded that although various IR and VI image fusion methods have been proposed, there still exist further improvements or potential research directions in different applications of IR andVI image fusion.
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Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network
TL;DR: Tang et al. as discussed by the authors proposed a semantic-aware real-time image fusion network (SeAFusion), which cascaded the image fusion module and semantic segmentation module and leveraged the semantic loss to guide high-level semantic information to flow back to the fusion module.
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Infrared Dim and Small Target Detection Based on Stable Multisubspace Learning in Heterogeneous Scene
TL;DR: A novel method named stable multisubspace learning is presented to deal with IR dim and small target detection in a highly complex background that takes into account the inner structure of actual images so that it overcomes the shortage of the traditional method.
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PIAFusion: A progressive infrared and visible image fusion network based on illumination aware
TL;DR: Tang et al. as mentioned in this paper proposed a progressive IR/VIS fusion method based on illumination aware, which adaptively maintains the intensity distribution of salient targets and preserves texture information in the background.
References
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Journal ArticleDOI
Robust principal component analysis
TL;DR: In this paper, the authors prove that under some suitable assumptions, it is possible to recover both the low-rank and the sparse components exactly by solving a very convenient convex program called Principal Component Pursuit; among all feasible decompositions, simply minimize a weighted combination of the nuclear norm and of the e1 norm.
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The contourlet transform: an efficient directional multiresolution image representation
Minh N. Do,Martin Vetterli +1 more
TL;DR: A "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information is pursued and it is shown that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves.
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A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography
Oleg Kuybeda,Gabriel A. Frank,Alberto Bartesaghi,Mario J. Borgnia,Sriram Subramaniam,Guillermo Sapiro +5 more
TL;DR: The genetic identity of each virus particle present in the mixture can be assigned based solely on the structural information derived from single envelope glycoproteins displayed on the virus surface by the nuclear norm-based, collaborative alignment method presented here.
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The Nonsubsampled Contourlet Transform: Theory, Design, and Applications
TL;DR: This paper proposes a design framework based on the mapping approach, that allows for a fast implementation based on a lifting or ladder structure, and only uses one-dimensional filtering in some cases.
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Objective image fusion performance measure
Costas Xydeas,Vladimir Petrovic +1 more
TL;DR: Experimental results clearly indicate that this metric reflects the quality of visual information obtained from the fusion of input images and can be used to compare the performance of different image fusion algorithms.