☆ 4.6 Article

Multi-Sensor Medical-Image Fusion Technique Based on Embedding Bilateral Filter in Least Squares and Salient Detection

SENSORS (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Artificial Intelligence

Brain tumor segmentation based on the fusion of deep semantics and edge information in multimodal MRI

Zhiqin Zhu et al.

Summary: In this paper, a brain tumor segmentation method based on the fusion of deep semantics and edge information in multimodal MRI is proposed. The method utilizes Swin Transformer for semantic feature extraction, introduces a shifted patch tokenization strategy, and designs an edge spatial attention block and a multi-feature inference block based on graph convolution for feature enhancement and fusion. The experimental results demonstrate that the proposed method outperforms other methods in brain tumor segmentation.

INFORMATION FUSION (2023)

添加到收藏夹

Article Computer Science, Information Systems

IFSepR: A General Framework for Image Fusion Based on Separate Representation Learning

Xiaoqing Luo et al.

Summary: This paper proposes a novel image fusion framework called IFSepR based on separate representation learning. By exploiting the common and private features of co-modal and multi-modal images, the disentangled representation is utilized to help with image fusion, specifically the fusion rule design. The proposed model incorporates an autoencoder network and contrastive learning to build a multi-branch encoder with contrastive constraints, allowing for the learning of common and private features of paired images. Through quantitative and qualitative comparisons with state-of-art image fusion methods on three typical fusion tasks, the advantages of the proposed model are demonstrated.

IEEE TRANSACTIONS ON MULTIMEDIA (2023)

添加到收藏夹

Article Computer Science, Artificial Intelligence

U2Fusion: A Unified Unsupervised Image Fusion Network

Han Xu et al.

Summary: This study proposes a novel unified and unsupervised end-to-end image fusion network, U2Fusion, which can solve different fusion problems. By training the model with adaptive information preservation, the network avoids the requirements of previous image fusion methods and has broad applicability. Moreover, a new dataset RoadScene is released for evaluation and comparison.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2022)

添加到收藏夹

Article Automation & Control Systems

FCFusion: Fractal Componentwise Modeling With Group Sparsity for Medical Image Fusion

Guoxia Xu et al.

Summary: This article presents a novel framework combining fractal constraint with group sparsity for multimodal image fusion. The experiments show that the framework has better performance in quantitative visual quality and qualitative evaluation analysis.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2022)

添加到收藏夹

Article Computer Science, Information Systems

Medical Image Fusion and Denoising Algorithm Based on a Decomposition Model of Hybrid Variation-Sparse Representation

Guofen Wang et al.

Summary: This paper proposes a novel medical image fusion and denoising algorithm that effectively solves problems such as excessive blur, unclean denoising, gradient information loss, and color distortion. The algorithm has been proven to outperform other algorithms through numerous experiments.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2022)

添加到收藏夹

Article Automation & Control Systems

SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer

Jiayi Ma et al.

Summary: This study proposes a novel image fusion framework called SwinFusion, which combines cross-domain long-range learning and Swin Transformer. The framework integrates complementary information and achieves global interaction through attention-guided cross-domain modules. It also addresses multi-scene image fusion problems by preserving structure, detail, and intensity. Extensive experiments prove the superiority of SwinFusion compared to other state-of-the-art fusion algorithms. The implementation code and pre-trained weights are available at https://github.com/Linfeng-Tang/SwinFusion.

IEEE-CAA JOURNAL OF AUTOMATICA SINICA (2022)

添加到收藏夹

Article Engineering, Multidisciplinary

Tri-modal medical image fusion based on adaptive energy choosing scheme and sparse representation

Yuchan Jie et al.

Summary: This paper proposes a novel tri-modal medical image fusion method based on cartoon-texture decomposition, using a rolling guidance filter and sparse representation to fuse the texture components. A new adaptive energy choosing scheme is also proposed to fuse the cartoon components. Experimental results demonstrate that the proposed method outperforms some state-of-the-art methods in subjective and objective assessments.

MEASUREMENT (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

EMFusion: An unsupervised enhanced medical image fusion network

Han Xu et al.

Summary: This paper proposes an unsupervised enhanced medical image fusion network that preserves information through surface-level and deep-level constraints, while also enhancing the chrominance information of fusion results.

INFORMATION FUSION (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Image fusion meets deep learning: A survey and perspective

Hao Zhang et al.

Summary: Image fusion aims to extract and combine meaningful information from different source images to generate a single informative image. The development of deep learning, with techniques like generative adversarial networks and autoencoders, has significantly advanced image fusion. However, a comprehensive review of the latest deep-learning methods in different fusion scenarios is lacking, which is addressed in this survey.

INFORMATION FUSION (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Attribute filter based infrared and visible image fusion

Yan Mo et al.

Summary: A novel infrared and visible image fusion method is proposed in this paper, which considers the attributes of objects in source images and utilizes edge-preserving filters and weight-based pyramid fusion strategy to achieve more natural fusion results. Experimental results demonstrate that the proposed method achieves state-of-the-art fusion performance in terms of both visual and objective evaluations. The algorithm is also implemented in an infrared-visible dual sensor system, showing the practicality of the fusion method.

INFORMATION FUSION (2021)

添加到收藏夹

Article Engineering, Electrical & Electronic

Multi-focus image fusion based on nonsubsampled contourlet transform and residual removal

Xiaosong Li et al.

Summary: A novel multi-focus image fusion method based on residual removal is proposed in this paper, which effectively bridges the gap between transform domain and spatial domain methods, successfully addressing the challenge of erasing defocused pixels. Experimental results demonstrate that the proposed method outperforms some state-of-the-art methods in both quantitative and qualitative evaluations.

SIGNAL PROCESSING (2021)

添加到收藏夹

Article Computer Science, Information Systems

Multimodal medical image fusion based on joint bilateral filter and local gradient energy

Xiaosong Li et al.

Summary: Multimodal medical image fusion is an important technique for biomedical diagnosis, and a novel method with two-layer decomposition and local gradient energy operator is proposed in this paper to achieve better fusion performance and computational efficiency. Extensive experiments demonstrate the method's superiority over state-of-the-art methods in both visual quality and quantitative evaluation.

INFORMATION SCIENCES (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

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

Hao Zhang et al.

Summary: This paper introduces a squeeze-and-decomposition network (SDNet) for real-time multi-modal and digital photography image fusion. By transforming fusion problems into extraction and reconstruction of gradient and intensity information, and introducing the squeeze and decomposition concept into image fusion, the method outperforms state-of-the-art techniques in subjective visual effect and quantitative metrics in various fusion tasks, while also being much faster for real-time fusion tasks.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Joint image fusion and denoising via three-layer decomposition and sparse representation

Xiaosong Li et al.

Summary: The proposed image fusion method is based on three-layer decomposition and sparse representation, which effectively fuses and denoises high-frequency components by adaptively designing sparse reconstruct error parameters. Additionally, the structure-texture decomposition model and carefully designed fusion rules are used to fully utilize details and energy in low-frequency components. The experimental results show that this method can effectively address clean and noisy image fusion problems and outperform some state-of-the-art methods in subjective visual and quantitative evaluations.

KNOWLEDGE-BASED SYSTEMS (2021)

添加到收藏夹

Review Engineering, Electrical & Electronic

Multimodal medical image fusion review: Theoretical background and recent advances

Haithem Hermessi et al.

Summary: The article discusses the development and application of medical image fusion methods, exploring the theoretical backgrounds and approaches of different fusion categories, summarizing the pros and cons of each category, and proposing directions for future research.

SIGNAL PROCESSING (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Localization of radiance transformation for image dehazing in wavelet domain

Hira Khan et al.

NEUROCOMPUTING (2020)

添加到收藏夹

Article Engineering, Electrical & Electronic

Embedding Bilateral Filter in Least Squares for Efficient Edge-Preserving Image Smoothing

Wei Liu et al.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

IFCNN: A general image fusion framework based on convolutional neural network

Yu Zhang et al.

INFORMATION FUSION (2020)

添加到收藏夹

Article Engineering, Electrical & Electronic

Laplacian Redecomposition for Multimodal Medical Image Fusion

Xiaoxiao Li et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

添加到收藏夹

Article Engineering, Electrical & Electronic

Medical Image Fusion With Parameter-Adaptive Pulse Coupled Neural Network in Nonsubsampled Shearlet Transform Domain

Ming Yin et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2019)

添加到收藏夹

Article Optics

Infrared and visible image perceptive fusion through multi-level Gaussian curvature filtering image decomposition

Wei Tan et al.

APPLIED OPTICS (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

FusionGAN: A generative adversarial network for infrared and visible image fusion

Jiayi Ma et al.

INFORMATION FUSION (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Infrared and visible image fusion methods and applications: A survey

Jiayi Ma et al.

INFORMATION FUSION (2019)

添加到收藏夹

Article Computer Science, Information Systems

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

Zhiqin Zhu et al.

IEEE ACCESS (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Image denoising with norm weighted fusion estimators

Nazeer Muhammad et al.

PATTERN ANALYSIS AND APPLICATIONS (2018)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Deep learning for pixel-level image fusion: Recent advances and future prospects

Yu Liu et al.

INFORMATION FUSION (2018)

添加到收藏夹

Review Computer Science, Artificial Intelligence

Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review

Qiang Zhang et al.

INFORMATION FUSION (2018)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Anatomical-Functional Image Fusion by Information of Interest in Local Laplacian Filtering Domain

Jiao Du et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2017)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Pixel-level image fusion: A survey of the state of the art

Shutao Li et al.

INFORMATION FUSION (2017)

添加到收藏夹

Article Instruments & Instrumentation

Infrared and visible image fusion based on visual saliency map and weighted least square optimization

Jinlei Ma et al.

INFRARED PHYSICS & TECHNOLOGY (2017)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Joint Convolutional Analysis and Synthesis Sparse Representation for Single Image Layer Separation

Shuhang Gu et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Robust Multi-Focus Image Fusion Using Multi-Task Sparse Representation and Spatial Context

Qiang Zhang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)

添加到收藏夹

Article Instruments & Instrumentation

Fusion method for infrared and visible images by using non-negative sparse representation

Jun Wang et al.

INFRARED PHYSICS & TECHNOLOGY (2014)

添加到收藏夹

Article Engineering, Biomedical

Group-Sparse Representation With Dictionary Learning for Medical Image Denoising and Fusion

Shutao Li et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2012)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study

Zheng Liu et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2012)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Evaluation of focus measures in multi-focus image fusion

Wei Huang et al.

PATTERN RECOGNITION LETTERS (2007)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Image information and visual quality

HR Sheikh et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2006)

添加到收藏夹

Article Mathematics, Applied

A nonlinear correlation measure for multivariable data set

Q Wang et al.

PHYSICA D-NONLINEAR PHENOMENA (2005)

添加到收藏夹

Article Engineering, Electrical & Electronic

Information measure for performance of image fusion

GH Qu et al.

ELECTRONICS LETTERS (2002)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.