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Journal ArticleDOI

Objective image fusion performance measure

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TLDR
Experimental results clearly indicate that this metric reflects the quality of visual information obtained from the fusion of input images and can be used to compare the performance of different image fusion algorithms.
Abstract
A measure for objectively assessing the pixel level fusion performance is defined. The proposed metric reflects the quality of visual information obtained from the fusion of input images and can be used to compare the performance of different image fusion algorithms. Experimental results clearly indicate that this metric is perceptually meaningful.

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Citations
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Journal ArticleDOI

An object-level strategy for pan-sharpening quality assessment of high-resolution satellite imagery

TL;DR: By applying image fusion quality metrics (IFQMs) to image objects, an object- level strategy for quality assessment of the image fusion process is proposed and experimental results show higher capabilities of object-level quality assessment strategy in the quality Assessment of the fusion process.
Proceedings ArticleDOI

Pixel-Level image Fusion Based on Fuzzy Theory

TL;DR: In this article, the low frequency band of the image multiscale representation is segmented into three kinds of regions by K-mean algorithm, which is used to determine the fusion rule and to achieve the multiscales representation of fusion result.
Journal ArticleDOI

Multi-Focus Fusion Technique on Low-Cost Camera Images for Canola Phenotyping.

TL;DR: A new multi-focus image fusion that exhibits a competitive performance and outperforms some other state-of-the-art methods based on the visual saliency maps and gradient domain fast guided filter is proposed.
Journal ArticleDOI

Quality assessment of multi-exposure image fusion by synthesizing local and global intermediate references

TL;DR: In this article , the intermediate reference features are synthesized in gradient domain, structural tensor domain, and global perception domain, respectively, and a single quality measure is estimated to reflect the visual quality of the fused image from a specific perspective.
Journal ArticleDOI

Multi-Sensor Image Fusion: A Survey of the State of the Art

TL;DR: A comprehensive survey of the state of the art of multi-sensor image fusion methods in terms of three aspects: pixel- level fusion, feature-level fusion and decision-level fuse is provided.
References
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Journal ArticleDOI

Multisensor image fusion using the wavelet transform

TL;DR: In this article, an image fusion scheme based on the wavelet transform is presented, where wavelet transforms of the input images are appropriately combined, and the new image is obtained by taking the inverse wavelet transformation of the fused wavelet coefficients.
Book

The Perception of Visual Information

TL;DR: This book examines the current status of what is known (and not known) about human vision, how human observers interpret visual data, and how to present such data to facilitate their interpretation and use.
Proceedings ArticleDOI

Cross-band pixel selection in multiresolution image fusion

TL;DR: Preliminary subjective image fusion results demonstrate clearly the advantage which the proposed cross-band selection technique offers, when compared to conventional area based pixel selection.
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