Mr. Xin Nie Profile

Xin Nie

at Wuhan Univ of Technology

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 9 August 2018 Paper

Space-variant text image deblurring with nonconvex constraint

Xin Nie, Ryan Wen Liu, Tongwei Lu

Proceedings Volume 10806, 1080626 (2018) https://doi.org/10.1117/12.2502947

KEYWORDS: Cameras, Image restoration, Image quality, Imaging systems, Image processing, Motion models, Visual process modeling, Digital cameras, Machine vision, Computer vision technology

Read Abstract +

Due to the relative motion between camera and scene to be photographed during exposure, image deblurring is commonly categorized into two types: space-invariant and space-variant versions. Space-variant image deblurring is more difficult since the blurring effect cannot be modeled by convolution. In this paper, we mainly focus on the problem of space-variant text image deblurring. To guarantee high-quality imaging, hyper-Laplacian prior is exploited to model the distribution of text image gradients. Under the maximum a posteriori (MAP) estimation framework, we propose to develop a nonconvex variational model to handle the problem of space-variant text image deblurring. The proposed method has the capacity of suppressing the undesirable space-variant blurring effect and ringing artifacts while preserving the main structural features. Several experiments will be conducted to compare our method with two popular image deblurring methods. Numerical results have demonstrated the superior performance of the proposed method in terms of PSNR, ISNR, MSSIM and visual quality assessments.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years