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This article presents an image deblurring method using &#x2113;0-norm-based deblurring and &#x2113;2-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 &#x2113;0-norm-based deblurring using the intensity and dark channel priors. Although the &#x2113;0-norm-based deblurring can provide a significantly restored result, it cannot overcome the loss of the texture region. On the other hand, the proposed &#x2113;2-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.

ieee journal of selected topics in applied earth observations and remote sensing

Texture-Aware Deblurring for Remote Sensing Images Using <inline-formula><tex-math notation="LaTeX">$ \ell _0$</tex-math></inline-formula>-Based Deblurring and <inline-formula><tex-math notation="LaTeX">$ \ell _2$</tex-math></inline-formula>-Based Fusion

Texture-Aware Deblurring for Remote Sensing Images Using $ \ell _0$-Based Deblurring and $ \ell _2$-Based Fusion