Regular Articles

Removing blur kernel noise via a hybrid ℓp norm

[+] Author Affiliations
Xin Yu

Tsinghua University, Department of Electronic Engineering, No. 30 Shuang Tsing Road, Beijing 100084, China

Shunli Zhang

Tsinghua University, Department of Electronic Engineering, No. 30 Shuang Tsing Road, Beijing 100084, China

Xiaolin Zhao

Air Force Engineering University, No. 1 Chang Le Road, Xi’an 710043, China

Li Zhang

Tsinghua University, Department of Electronic Engineering, No. 30 Shuang Tsing Road, Beijing 100084, China

J. Electron. Imaging. 24(1), 013011 (Jan 09, 2015). doi:10.1117/1.JEI.24.1.013011
History: Received July 9, 2014; Accepted December 2, 2014
Text Size: A A A

Abstract.  When estimating a sharp image from a blurred one, blur kernel noise often leads to inaccurate recovery. We develop an effective method to estimate a blur kernel which is able to remove kernel noise and prevent the production of an overly sparse kernel. Our method is based on an iterative framework which alternatingly recovers the sharp image and estimates the blur kernel. In the image recovery step, we utilize the total variation (TV) regularization to recover latent images. In solving TV regularization, we propose a new criterion which adaptively terminates the iterations before convergence. While improving the efficiency, the quality of the final results is not degraded. In the kernel estimation step, we develop a metric to measure the usefulness of image edges, by which we can reduce the ambiguity of kernel estimation caused by small-scale edges. We also propose a hybrid p norm, which is composed of 2 norm and p norm with 0.7p<1, to construct a sparsity constraint. Using the hybrid p norm, we reduce a wider range of kernel noise and recover a more accurate blur kernel. The experiments show that the proposed method achieves promising results on both synthetic and real images.

© 2015 SPIE and IS&T

Citation

Xin Yu ; Shunli Zhang ; Xiaolin Zhao and Li Zhang
"Removing blur kernel noise via a hybrid ℓp norm", J. Electron. Imaging. 24(1), 013011 (Jan 09, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.1.013011


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement


 

  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.