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- W3040583619 abstract "Image fusion is a process that integrates similar types of images collected from heterogeneous sources into one image in which the information is more definite and certain. Hence, the resultant image is anticipated as more explanatory and enlightening both for human and machine perception. Different image combination methods have been presented to consolidate significant data from a collection of images into one image. As a result of its applications and advantages in variety of fields such as remote sensing, surveillance, and medical imaging, it is significant to comprehend image fusion algorithms and have a comparative study on them. This paper presents a review of the present state-of-the-art and well-known image fusion techniques. The performance of each algorithm is assessed qualitatively and quantitatively on two benchmark multi-focus image datasets. We also produce a multi-focus image fusion dataset by collecting the widely used test images in different studies. The quantitative evaluation of fusion results is performed using a set of image fusion quality assessment metrics. The performance is also evaluated using different statistical measures. Another contribution of this paper is the proposal of a multi-focus image fusion library, to the best of our knowledge, no such library exists so far. The library provides implementation of numerous state-of-the-art image fusion algorithms and is made available publicly at project website." @default.
- W3040583619 created "2020-07-10" @default.
- W3040583619 creator A5039298911 @default.
- W3040583619 creator A5039541296 @default.
- W3040583619 creator A5081484066 @default.
- W3040583619 date "2020-07-02" @default.
- W3040583619 modified "2023-09-30" @default.
- W3040583619 title "Multi-Focus Image Fusion: Algorithms, Evaluation, and a Library" @default.
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- W3040583619 doi "https://doi.org/10.3390/jimaging6070060" @default.
- W3040583619 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8321074" @default.
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- W3040583619 hasPublicationYear "2020" @default.
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