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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

CNNs hard voting for multi-focus image fusion

TL;DR: The proposed convolution neural networks based on ensemble learning for multi-focus image fusion have the cleanest initial decision map and the best quality of the output fused image compared to the other state of the art methods.
Journal ArticleDOI

Regularized super-resolution image reconstruction employing robust error norms

TL;DR: The proposed TTV, LTV, and HTV methods are directly compared with a former SR method that employs the L1-norm in the data-fidelity term for synthesized and real sequences of frames, and results verify the robust statistics theory.
Proceedings ArticleDOI

Multimodal image fusion via sparse representation and clustering-based dictionary learning algorithm in NonSubsampled Contourlet domain

TL;DR: The experimental results demonstrate effectiveness of the proposed dictionary learning algorithm and priority of general framework, in terms of both subjective and objective evaluation for image fusion task.
Journal ArticleDOI

Multi-focus image fusion using fractal dimension.

TL;DR: A translation-invariant multi-focus image fusion approach using the à-trous wavelet transform is introduced, which uses fractal dimension as a clarity measure for the approximation coefficients and Otsu's threshold to fuse the detail coefficients.
Journal ArticleDOI

Infrared and visual image fusion based on multi-scale feature decomposition

TL;DR: A novel IR and VI image fusion method based on multi-scale feature decomposition (MSFD), which separates image features more effectively and demonstrates the advantages of the proposed method over other compared methods in term of visual observation and evaluation metrics.
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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