Local statistics based filtering method for enhancement in super-resolution image reconstruction

Numan Unaldi; Vijayan K. Asari

doi:10.1117/12.722134

25 April 2007 Local statistics based filtering method for enhancement in super-resolution image reconstruction

Numan Unaldi, Vijayan K. Asari

Proceedings Volume 6575, Visual Information Processing XVI; 657508 (2007) https://doi.org/10.1117/12.722134
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

A local statistics based contrast enhancement technique for enhancing the reconstructed high resolution image from a set of shifted and rotated low resolution images is proposed in this paper. Planar shifts and rotations in the low resolution images are determined by a phase correlation approach performed on the polar coordinate representations of their Fourier transforms. The pixels of the low resolution images are expressed in the coordinate frame of the reference image and the image values are interpolated on a regular high-resolution grid. The non-uniform interpolation technique which allows for the reconstruction of functions from samples taken at non-uniformly distributed locations has relatively low computational complexity. Since bi-cubic interpolation produces blurred edges due to its averaging effect, the edges of the reconstructed image are enhanced using a local statistics based approach. The center-surround ratio is adjusted using global statistics of the reconstructed image and used as an adaptive gamma correction to achieve the local contrast enhancement which increases the image sharpness. Performance of the proposed algorithm is evaluated by conducting experiments on both synthetic and real image sets and the results are encouraging in terms of visual quality.

Citation Download Citation

Numan Unaldi and Vijayan K. Asari "Local statistics based filtering method for enhancement in super-resolution image reconstruction", Proc. SPIE 6575, Visual Information Processing XVI, 657508 (25 April 2007); https://doi.org/10.1117/12.722134

ACCESS THE FULL ARTICLE

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