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Image fusion via dynamic gradient sparsity and anisotropic spectral-spatial total variation | IEEE Conference Publication | IEEE Xplore

Image fusion via dynamic gradient sparsity and anisotropic spectral-spatial total variation


Abstract:

In this paper, we develop a sparsity based model for the fusion of a high spatial-resolution image and a multispectral image. The given model is based on the combination ...Show More

Abstract:

In this paper, we develop a sparsity based model for the fusion of a high spatial-resolution image and a multispectral image. The given model is based on the combination of a dynamic gradient sparsity (DGS) and an anisotropic spectral-spatial total variation (ASSTV). We design an alternating direction method of multipliers (ADMM) based algorithm to solve the proposed model. In contrast to existing approaches, the proposed method can generate more spatial details as well as preserve favorable spectral information. Experimental results demonstrate that the proposed approach outperforms several state-of-the-art image fusion methods both quantitatively and visually, in terms of both pansharpening application of remote sensing images and fusion application of natural color images.
Date of Conference: 17-20 September 2017
Date Added to IEEE Xplore: 22 February 2018
ISBN Information:
Electronic ISSN: 2381-8549
Conference Location: Beijing, China

References

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