Texture-Aware Deblurring for Remote Sensing Images Using ℓ0-Based Deblurring and ℓ2-Based Fusion

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Abstract

This article presents an image deblurring method using ℓ0-norm-based deblurring and ℓ2-norm-based texture-aware image fusion for remote sensing images. To restore the details of blurred texture, the proposed method first performs texture restoration by fusing the restored results using Richardson-Lucy deconvolution and unsharp masking. Next, we analyzed the intensity and dark channel properties of remote sensing images and perform the ℓ0-norm-based deblurring using the intensity and dark channel priors. Although the ℓ0-norm-based deblurring can provide a significantly restored result, it cannot overcome the loss of the texture region. On the other hand, the proposed ℓ2-norm-based image fusion method can preserve both sharp edges and texture details. In the experiments, we demonstrate that the proposed method can provide better restored results than existing state-of-the-art deblurring methods without oversmoothing and undesired artifact.

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APA

Lim, H., Yu, S., Park, K., Seo, D., & Paik, J. (2020). Texture-Aware Deblurring for Remote Sensing Images Using ℓ0-Based Deblurring and ℓ2-Based Fusion. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 3094–3108. https://doi.org/10.1109/JSTARS.2020.2999961

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