Ms. Na Liu Profile

Na Liu

at Beijing Institute 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 | 30 October 2009 Paper

A novel super-resolution image fusion algorithm based on improved PCNN and wavelet transform

Na Liu, Yajun Song

Proceedings Volume 7496, 749621 (2009) https://doi.org/10.1117/12.833925

KEYWORDS: Image fusion, Super resolution, Neurons, Wavelet transforms, Visual process modeling, Image processing, Reconstruction algorithms, Image resolution, Visualization, Image processing algorithms and systems

Read Abstract +

Super-resolution reconstruction technology is to explore new information between the under-sampling image series obtained from the same scene and to achieve the high-resolution picture through image fusion in sub-pixel level. The traditional super-resolution fusion methods for sub-sampling images need motion estimation and motion interpolation and construct multi-resolution pyramid to obtain high-resolution, yet the function of the human beings' visual features are ignored. In this paper, a novel resolution reconstruction for under-sampling images of static scene based on the human vision model is considered by introducing PCNN (Pulse Coupled Neural Network) model, which simplifies and improves the input model, internal behavior and control parameters selection. The proposed super-resolution image fusion algorithm based on PCNN-wavelet is aimed at the down-sampling image series in a static scene. And on the basis of keeping the original features, we introduce Relief Filter(RF) to the control and judge segment to overcome the effect of random factors(such as noise, etc) effectively to achieve the aim that highlighting interested object though the fusion. Numerical simulations show that the new algorithm has the better performance in retaining more details and keeping high resolution.

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