LAUSR

Kernel Estimation of a Characteristic Function

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0 Published in 2017 at "Journal of Mathematical Sciences"

DOI: 10.1007/s10958-016-3207-1

Abstract: This article deals with the study of asymptotic properties of a nonparametric kernel estimator of a characteristic function. Uniformly strong consistency of kernel estimator with fixed and expanding interval is established. The law of iterated… read more here.

Keywords: function; kernel estimation; estimation characteristic; characteristic function ... See more keywords

Accurate blind deblurring using salientpatch-based prior for large-size images

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0 Published in 2018 at "Multimedia Tools and Applications"

DOI: 10.1007/s11042-018-6009-2

Abstract: The full-image based kernel estimation strategy is usually susceptible by the smooth and fine-scale background regions impacting and it is time-consuming for large-size image deblurring. Since not all the pixels in the blurred image are… read more here.

Keywords: large size; salientpatch based; size; kernel estimation ... See more keywords

Blur kernel estimation using sparsity and local smoothness prior

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1 Published in 2017 at "Journal of Electronic Imaging"

DOI: 10.1117/1.jei.26.3.033024

Abstract: Abstract. Since blur kernel estimation is an ill-posed problem, it is essential that it be constrained by parametric image priors. However, the previous normalized sparsity measure alters the kernel structure during estimation. To address the… read more here.

Keywords: estimation; smoothness prior; kernel estimation; blur kernel ... See more keywords

Blur Kernel Estimation by Structure Sparse Prior

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1 Published in 2020 at "Applied Sciences"

DOI: 10.3390/app10020657

Abstract: Blind image deblurring tries to recover a sharp version from a blurred image, where blur kernel is usually unknown. Recently, sparse representation has been successfully applied to estimate the blur kernel. However, the sparse representation… read more here.

Keywords: sparse representation; kernel estimation; blur kernel; structure ... See more keywords

Kernel Estimation of the Extropy Function under α-Mixing Dependent Data

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2 Published in 2023 at "Symmetry"

DOI: 10.3390/sym15040796

Abstract: Shannon developed the idea of entropy in 1948, which relates to the measure of uncertainty associated with a random variable X. The contribution of the extropy function as a dual complement of entropy is one… read more here.

Keywords: extropy; kernel estimation; extropy function; estimation extropy ... See more keywords