Pixel-level image fusion: A survey of the state of the art
Pixel-level image fusion: A survey of the state of the art
复制标题
DOI：
10.1016/j.inffus.2016.05.004
复制
发表时间：
2017-01-01
影响因子：
18.6
通讯作者：
Yin, Haitao
中科院分区：
文献类型：
--
作者：
Li, Shutao;Kang, Xudong;Yin, Haitao
像素级图像融合被设计为将多个输入图像联合收割机组合成融合图像，与任何输入图像相比，期望融合图像对于人类或机器感知而言具有更多信息。由于这种优势，像素级图像融合在遥感、医学成像和夜视应用中取得了显著的成就。在本文中，我们首先提供了一个全面的调查最先进的像素级图像融合方法。然后，总结了现有的融合质量度量方法。接下来，四个主要应用，即，遥感、医疗诊断、监视、摄影以及像素级图像融合应用的挑战。最后，本文总结了各种图像融合方法的研究现状，指出了图像融合在不同领域的应用前景。因此，图像融合领域的研究在未来几年仍有望显着增长。(C)2016爱思唯尔B.V.保留所有权利。
Pixel-level image fusion is designed to combine multiple input images into a fused image, which is expected to be more informative for human or machine perception as compared to any of the input images. Due to this advantage, pixel-level image fusion has shown notable achievements in remote sensing, medical imaging, and night vision applications. In this paper, we first provide a comprehensive survey of the state of the art pixel-level image fusion methods. Then, the existing fusion quality measures are summarized. Next, four major applications, i.e., remote sensing, medical diagnosis, surveillance, photography, and challenges in pixel-level image fusion applications are analyzed. At last, this review concludes that although various image fusion methods have been proposed, there still exist several future directions in different image fusion applications. Therefore, the researches in the image fusion field are still expected to significantly grow in the coming years. (C) 2016 Elsevier B.V. All rights reserved.