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A Phase Congruency and Local Laplacian Energy Based Multi-Modality Medical Image Fusion Method in NSCT Domain

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TLDR
A novel multi-modality medical image fusion method based on phase congruency and local Laplacian energy that achieves competitive performance in both the image quantity and computational costs is presented.
Abstract
Multi-modality image fusion provides more comprehensive and sophisticated information in modern medical diagnosis, remote sensing, video surveillance, and so on. This paper presents a novel multi-modality medical image fusion method based on phase congruency and local Laplacian energy. In the proposed method, the non-subsampled contourlet transform is performed on medical image pairs to decompose the source images into high-pass and low-pass subbands. The high-pass subbands are integrated by a phase congruency-based fusion rule that can enhance the detailed features of the fused image for medical diagnosis. A local Laplacian energy-based fusion rule is proposed for low-pass subbands. The local Laplacian energy consists of weighted local energy and the weighted sum of Laplacian coefficients that describe the structured information and the detailed features of source image pairs, respectively. Thus, the proposed fusion rule can simultaneously integrate two key components for the fusion of low-pass subbands. The fused high-pass and low-pass subbands are inversely transformed to obtain the fused image. In the comparative experiments, three categories of multi-modality medical image pairs are used to verify the effectiveness of the proposed method. The experiment results show that the proposed method achieves competitive performance in both the image quantity and computational costs.

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Citations
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Journal ArticleDOI

U2Fusion: A Unified Unsupervised Image Fusion Network.

TL;DR: Qualitative and quantitative experimental results on three typical image fusion tasks validate the effectiveness and universality of U2Fusion, a unified model that is applicable to multiple fusion tasks.
Journal ArticleDOI

U2Fusion: A Unified Unsupervised Image Fusion Network

TL;DR: U2Fusion as discussed by the authors proposes a unified and unsupervised end-to-end image fusion network, which is capable of solving different fusion problems, including multi-modal, multi-exposure, and multi-focus cases.
Journal ArticleDOI

A Novel Fast Single Image Dehazing Algorithm Based on Artificial Multiexposure Image Fusion

TL;DR: An image fusion-based algorithm to enhance the performance and robustness of image dehazing is proposed, based on a set of gamma-corrected underexposed images, and pixelwise weight maps are constructed by analyzing both global and local exposedness to guide the fusion process.
Journal ArticleDOI

Image Dehazing by an Artificial Image Fusion Method Based on Adaptive Structure Decomposition

TL;DR: The proposed image dehazing scheme can effectively eliminate the visual degradation caused by haze without the physical model inversion of haze formation and both apriori estimation of scene depth and the expensive refinement process of depth mapping can be avoided.
Journal ArticleDOI

SDNet: A Versatile Squeeze-and-Decomposition Network for Real-Time Image Fusion

TL;DR: A squeeze-and-decomposition network (SDNet) is proposed to realize multi-modal and digital photography image fusion in real time and is much faster than the state-of-the-arts, which can deal with real-time fusion tasks.
References
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Journal ArticleDOI

FSIM: A Feature Similarity Index for Image Quality Assessment

TL;DR: A novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features.
Journal ArticleDOI

The contourlet transform: an efficient directional multiresolution image representation

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.
Journal ArticleDOI

Image information and visual quality

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 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

Information measure for performance of image fusion

TL;DR: The results show that the measure represents how much information is obtained from the input images and is meaningful and explicit.
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