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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

Simple, Accurate, and Robust Nonparametric Blind Super-Resolution

verfasst von : Wen-Ze Shao, Michael Elad

Erschienen in: Image and Graphics

Verlag: Springer International Publishing

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Abstract

This paper proposes a simple, accurate, and robust approach to single image blind super-resolution (SR). This task is formulated as a functional to be minimized with respect to both an intermediate super-resolved image and a non- parametric blur-kernel. The proposed method includes a convolution consistency constraint which uses a non-blind learning-based SR result to better guide the estimation process. Another key component is the bi-ℓ0-ℓ2-norm regularization placed on the super-resolved, sharp image and the blur-kernel, which is shown to be quite beneficial for accurate blur-kernel estimation. The numerical optimization is implemented by coupling the splitting augmented Lagrangian and the conjugate gradient. With the pre-estimated blur-kernel, the final SR image is reconstructed using a simple TV-based non-blind SR method. The new method is demonstrated to achieve better performance than Michaeli and Irani [2] in both terms of the kernel estimation accuracy and image SR quality.

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Vorheriges Kapitel Segmentation of Intra-retinal Layers in 3D Optic Nerve Head Images
Nächstes Kapitel Simulation of Interaction Between Fluid and Deformable Bodies
Fußnoten
1
I.e., knowing the blur kernel.
 
2
In [31] the bi-ℓ0-ℓ2-norm regularization is shown to achieve state-of-the-art kernel estimation performance. Due to this reason as well as the similarity between blind deblurring and blind SR, we extend the bi-ℓ0-ℓ2-norm regularization for the nonparametric blind SR problem.
 
3
BCCB: block-circulant with circulant blocks.
 
4
The same meaning applies to \( c_{{\mathbf{k}}}^{i} \).
 
5
We should note that we have also selected a uniform set of parameter values for each of the formulations (8), (9) and (10), respectively, in order to optimize the obtained blind SR performance on a series of experiments. However, it was found that these alternative are still inferior to (7), just similar to the observation made in blind motion deblurring [31].
 
6
Experiments reported in this paper are performed with MATLAB v7.0 on a computer with an Intel i7-4600 M CPU (2.90 GHz) and 8 GB memory.
 
7
In [2] blur-kernels are typically solved with size 9 × 9, 11 × 11 or 13 × 13 for various blind SR problems.
 
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Metadaten
Titel
Simple, Accurate, and Robust Nonparametric Blind Super-Resolution
verfasst von
Wen-Ze Shao
Michael Elad
Copyright-Jahr
2015
Verlag
Springer International Publishing
Buch
Image and Graphics

Print ISBN: 978-3-319-21968-4

Electronic ISBN: 978-3-319-21969-1

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-21969-1_29

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