Journal ArticleDOI
Multi-focus: Focused region finding and multi-scale transform for image fusion
TLDR
A novel multi-focus image fusion method based on a focused regions boundary finding and multi-scale transform (MST) is proposed, which can accurately determine the focused regions, and at the same time, a better fused boundary region can be obtained.About:
This article is published in Neurocomputing.The article was published on 2018-12-03. It has received 30 citations till now. The article focuses on the topics: Image fusion & Contourlet.read more
Citations
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Journal ArticleDOI
Multi-focus image fusion: A Survey of the state of the art
TL;DR: A comprehensive overview of existing multi-focus image fusion methods is presented and a new taxonomy is introduced to classify existing methods into four main categories: transformdomain methods, spatial domain methods, methods combining transform domain and spatial domain, and deep learning methods.
Journal ArticleDOI
A fuzzy convolutional neural network for enhancing multi-focus image fusion
TL;DR: In this article , a multi-focus image fusion (MFIF) method is employed to generate the fused image by integrating the fuzzy sets (FS) and convolutional neural network (CNN) to detect focused and unfocused parts in both source images.
Journal ArticleDOI
Fractal dimension based parameter adaptive dual channel PCNN for multi-focus image fusion
TL;DR: A transform domain multi-focus image fusion method based on a novel parameter adaptive DCPCNN (PA-DCPCNN) model, in which the parameters are adaptively estimated using the inputs, is proposed.
Journal ArticleDOI
Using Taylor Expansion and Convolutional Sparse Representation for Image Fusion
TL;DR: A novel method based on Taylor expansion and convolutional sparse representation (TE-CSR) and the inverse Taylor expansion to reconstruct the fused image to suppress the gap of image descriptions in existing decomposition based algorithms.
Journal ArticleDOI
Two-scale decomposition-based multifocus image fusion framework combined with image morphology and fuzzy set theory
TL;DR: A framework based on the fuzzy set theory to handle the vague features of image fusion processes, and a set of hybrid optimization methods is also designed to improve the performance.
References
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Journal ArticleDOI
Mean shift: a robust approach toward feature space analysis
Dorin Comaniciu,Peter Meer +1 more
TL;DR: It is proved the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density.
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Image information and visual quality
Hamid R. Sheikh,Alan C. Bovik +1 more
TL;DR: An image information measure is proposed that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image and combined these two quantities form a visual information fidelity measure for image QA.
Journal ArticleDOI
The dual-tree complex wavelet transform
TL;DR: Several methods for filter design are described for dual-tree CWT that demonstrates with relatively short filters, an effective invertible approximately analytic wavelet transform can indeed be implemented using the dual- tree approach.
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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.
Journal ArticleDOI
Image Fusion With Guided Filtering
Shutao Li,Xudong Kang,Jianwen Hu +2 more
TL;DR: Experimental results demonstrate that the proposed method can obtain state-of-the-art performance for fusion of multispectral, multifocus, multimodal, and multiexposure images.