A review of image fusion: Methods, applications and performance metrics

IF 3 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Simrandeep Singh , Harbinder Singh , Gloria Bueno , Oscar Deniz , Sartajvir Singh , Himanshu Monga , P.N. Hrisheekesha , Anibal Pedraza
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引用次数: 7

Abstract

The same sensor or a number of image sensors are used to take a series of photographs in order to gather as much data as possible about the scene. Several imaging techniques are used to retrieve entire information from the source under observation. Image fusion (IF) is used to create a new image that incorporates comprehensive information from many photographs. The various images may be captured from different viewpoints, different imaging sensors i.e., visible (VIS) and IR camera, different modalities i.e., computed tomography (CT) and magnetic resonance image (MRI), hyper spectral images i.e., panchromatic and multi-spectral satellite images, multi-exposure images and multi-focus images. Owing to the growing mandates and development of image enhancement schemes, numerous fusion methods were recently formulated. Consequentially, we are doing a survey study to document the methodological development in IF techniques. The outline of picture merging technologies is described in this article. Ultimately, latest state-of-the-art fusion techniques are also demonstrated. Readers will gain insights on current discoveries and their implications for the future through a review of diverse image fusion in various areas and fusion quality metrics.

图像融合技术综述:方法、应用和性能指标
使用相同的传感器或多个图像传感器来拍摄一系列照片,以便收集尽可能多的关于场景的数据。几种成像技术被用于从被观察的源中检索整个信息。图像融合(IF)用于创建一个新的图像,该图像包含来自许多照片的综合信息。可以从不同的视点、不同的成像传感器(即可见光(VIS)和IR相机)、不同的模态(即计算机断层扫描(CT)和磁共振图像(MRI))、超光谱图像(即全色和多光谱卫星图像)、多曝光图像和多焦点图像捕获各种图像。由于图像增强方案的需求和发展,最近制定了许多融合方法。因此,我们正在进行一项调查研究,以记录IF技术的方法发展。本文介绍了图像融合技术的概况。最后,还展示了最先进的聚变技术。读者将通过对不同领域的不同图像融合和融合质量指标的回顾,深入了解当前的发现及其对未来的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Digital Signal Processing
Digital Signal Processing 工程技术-工程:电子与电气
CiteScore
5.30
自引率
17.20%
发文量
435
审稿时长
66 days
期刊介绍: Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,
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