A Novel Multi-Modality Image Simultaneous Denoising and Fusion Method Based on Sparse Representation
Computers, 2021 Multi-modality image fusion applied to improve image quality has drawn great attention from researchers in recent years. However, noise is actually generated in images captured by different types of imaging sensors, which can seriously affect the ...
Guanqiu Qi +4 more
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Digital Image Progressive Fusion Method Based on Discrete Cosine Transform
Journal of Mathematics, 2023 The current progressive fusion methods for digital images have poor denoising performance, which leads to a decrease in image quality after progressive fusion.
Jiezi Chen
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Image Fusion Techniques: A Survey [PDF]
Archives of Computational Methods in Engineering, 2021 The necessity of image fusion is growing in recently in image processing applications due to the tremendous amount of acquisition systems. Fusion of images is defined as an alignment of noteworthy Information from diverse sensors using various mathematical models to generate a single compound image.
Harpreet Kaur +2 more
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NestFuse: An Infrared and Visible Image Fusion Architecture Based on Nest Connection and Spatial/Channel Attention Models [PDF]
IEEE Transactions on Instrumentation and Measurement, 2020 In this article, we propose a novel method for infrared and visible image fusion where we develop nest connection-based network and spatial/channel attention models.
Hui Li, Xiaojun Wu, T. Durrani
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Nonlinear Spectral Image Fusion [PDF]
, 2017 In this paper we demonstrate that the framework of nonlinear spectral decompositions based on total variation (TV) regularization is very well suited for image fusion as well as more general image manipulation tasks. The well-localized and edge-preserving spectral TV decomposition allows to select frequencies of a certain image to transfer particular ...
Benning, Martin +6 more
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FuseVis: Interpreting Neural Networks for Image Fusion Using Per-Pixel Saliency Visualization
Computers, 2020 Image fusion helps in merging two or more images to construct a more informative single fused image. Recently, unsupervised learning-based convolutional neural networks (CNN) have been used for different types of image-fusion tasks such as medical image ...
Nishant Kumar, Stefan Gumhold
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TGFuse: An Infrared and Visible Image Fusion Approach Based on Transformer and Generative Adversarial Network [PDF]
IEEE Transactions on Image Processing, 2022 The end-to-end image fusion framework has achieved promising performance, with dedicated convolutional networks aggregating the multi-modal local appearance.
Dongyu Rao, Xiaojun Wu, Tianyang Xu
semanticscholar +1 more source
General Image Fusion for an Arbitrary Number of Inputs Using Convolutional Neural Networks
Sensors, 2022 In this paper, we propose a unified and flexible framework for general image fusion tasks, including multi-exposure image fusion, multi-focus image fusion, infrared/visible image fusion, and multi-modality medical image fusion. Unlike other deep learning-
Yifan Xiao +3 more
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An Image Decomposition Fusion Method for Medical Images [PDF]
Mathematical Problems in Engineering, 2020 A fusion method based on the cartoon+texture decomposition method and convolution sparse representation theory is proposed for medical images. It can be divided into three steps: firstly, the cartoon and texture parts are obtained using the improved cartoon-texture decomposition method.
Lihong Chang, Wan Ma, Yu Jin, Li Xu
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Infrared and visible image fusion based on particle swarm optimization and dense block
Frontiers in Energy Research, 2022 Infrared and visible image fusion aims to preserve essential thermal information and crucial visible details from two types of input images to generate an informative fusion image for better visual perception. In recent years, several hybrid methods have
Jing Zhang +3 more
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