A no-reference perceptual blurriness metric based fast super-resolution of still pictures using sparse representation

Jae-Seok Choi; Sung-Ho Bae; Munchurl Kim

doi:10.1117/12.2083327

12 March 2015 A no-reference perceptual blurriness metric based fast super-resolution of still pictures using sparse representation

Jae-Seok Choi, Sung-Ho Bae, Munchurl Kim

Author Affiliations +

Proceedings Volume 9401, Computational Imaging XIII; 94010N (2015) https://doi.org/10.1117/12.2083327
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

In recent years, perceptually-driven super-resolution (SR) methods have been proposed to lower computational complexity. Furthermore, sparse representation based super-resolution is known to produce competitive high-resolution images with lower computational costs compared to other SR methods. Nevertheless, super-resolution is still difficult to be implemented with substantially low processing power for real-time applications. In order to speed up the processing time of SR, much effort has been made with efficient methods, which selectively incorporate elaborate computation algorithms for perceptually sensitive image regions based on a metric, such as just noticeable distortion (JND). Inspired by the previous works, we first propose a novel fast super-resolution method with sparse representation, which incorporates a no-reference just noticeable blur (JNB) metric. That is, the proposed fast super-resolution method efficiently generates super-resolution images by selectively applying a sparse representation method for perceptually sensitive image areas which are detected based on the JNB metric. Experimental results show that our JNB-based fast super-resolution method is about 4 times faster than a non-perceptual sparse representation based SR method for 256× 256 test LR images. Compared to a JND-based SR method, the proposed fast JNB-based SR method is about 3 times faster, with approximately 0.1 dB higher PSNR and a slightly higher SSIM value in average. This indicates that our proposed perceptual JNB-based SR method generates high-quality SR images with much lower computational costs, opening a new possibility for real-time hardware implementations.

Citation Download Citation

Jae-Seok Choi, Sung-Ho Bae, and Munchurl Kim "A no-reference perceptual blurriness metric based fast super-resolution of still pictures using sparse representation", Proc. SPIE 9401, Computational Imaging XIII, 94010N (12 March 2015); https://doi.org/10.1117/12.2083327

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