A survey of infrared and visual image fusion methods
Infrared (IR) and visual (VI) image fusion is designed to fuse multiple source images into a
comprehensive image to boost imaging quality and reduce redundancy information, which is …
comprehensive image to boost imaging quality and reduce redundancy information, which is …
From multi-scale decomposition to non-multi-scale decomposition methods: a comprehensive survey of image fusion techniques and its applications
Image fusion is a well-recognized and a conventional field of image processing. Image
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …
Infrared and visible image fusion methods and applications: A survey
Infrared images can distinguish targets from their backgrounds based on the radiation
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …
difference, which works well in all-weather and all-day/night conditions. By contrast, visible …
MFF-GAN: An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion
Multi-focus image fusion is an enhancement method to generate full-clear images, which
can address the depth-of-field limitation in imaging of optical lenses. Most existing methods …
can address the depth-of-field limitation in imaging of optical lenses. Most existing methods …
Semantic-supervised infrared and visible image fusion via a dual-discriminator generative adversarial network
Image fusion synthesizes a new image from multiple images of the same scene. The
synthesized image should be suitable for human visual perception and follow-up high-level …
synthesized image should be suitable for human visual perception and follow-up high-level …
Multi-focus image fusion using dictionary-based sparse representation
Multi-focus image fusion has emerged as a major topic in image processing to generate all-
focus images with increased depth-of-field from multi-focus photographs. Different …
focus images with increased depth-of-field from multi-focus photographs. Different …
FuseGAN: Learning to fuse multi-focus image via conditional generative adversarial network
We study the problem of multi-focus image fusion, where the key challenge is detecting the
focused regions accurately among multiple partially focused source images. Inspired by the …
focused regions accurately among multiple partially focused source images. Inspired by the …
Multifocus image fusion and restoration with sparse representation
B Yang, S Li - IEEE transactions on Instrumentation and …, 2009 - ieeexplore.ieee.org
To obtain an image with every object in focus, we always need to fuse images taken from the
same view point with different focal settings. Multiresolution transforms, such as pyramid …
same view point with different focal settings. Multiresolution transforms, such as pyramid …
Unified gradient-and intensity-discriminator generative adversarial network for image fusion
This study proposes a unified gradient-and intensity-discriminator generative adversarial
network for various image fusion tasks, including infrared and visible image fusion, medical …
network for various image fusion tasks, including infrared and visible image fusion, medical …
Performance comparison of different multi-resolution transforms for image fusion
S Li, B Yang, J Hu - Information Fusion, 2011 - Elsevier
Image fusion combines information from multiple images of the same scene to get a
composite image that is more suitable for human visual perception or further image …
composite image that is more suitable for human visual perception or further image …