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Improving high-pass fusion method using wavelets
In an appropriate image fusion method, spatial information of the panchr...
02/23/2017 ∙ by Hamid Reza Shahdoosti, et al. ∙
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Multi-focus Noisy Image Fusion using Low-Rank Representation
In the process of image acquisition, the noise is inevitable for source ...
04/25/2018 ∙ by Hui Li, et al. ∙
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Multi-Sensor Image Fusion Based on Moment Calculation
An image fusion method based on salient features is proposed in this pap...
12/05/2013 ∙ by Sourav Pramanik, et al. ∙
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Data Representation using the Weyl Transform
The Weyl transform is introduced as a rich framework for data representa...
12/18/2014 ∙ by Qiang Qiu, et al. ∙
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Fusion of Daubechies Wavelet Coefficients for Human Face Recognition
In this paper fusion of visual and thermal images in wavelet transformed...
07/05/2010 ∙ by Mrinal Kanti Bhowmik, et al. ∙
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A Low Complexity VLSI Architecture for Multi-Focus Image Fusion in DCT Domain
Due to the confined focal length of optical sensors, focusing all object...
09/15/2015 ∙ by Ashutosh Mishra, et al. ∙
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Image segmentation of cross-country scenes captured in IR spectrum
Computer vision has become a major source of information for autonomous ...
04/08/2016 ∙ by Artem Lenskiy, et al. ∙
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A New Multifocus Image Fusion Method Using Contourlet Transform
09/13/2017 ∙ by Fatemeh Vakili Moghadam, et al. ∙
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A new multifocus image fusion approach is presented in this paper. First the contourlet transform is used to decompose the source images into different components. Then, some salient features are extracted from components. In order to extract salient features, spatial frequency is used. Subsequently, the best coefficients from the components are selected by the maximum selection rule. Finally, the inverse contourlet transform is applied to the selected coefficients. Experiments show the superiority of the proposed method.
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