Earticle

초록

영어

A novel objective quality assessment method is proposed for super-resolution images in this manuscript. We not only estimate the preserved information of each spatial location in the super-resolution image by structural similarity, but also compute the local phase coherence (LPC) with which we can detect the image blur in the super-resolution image. After the preserved structural information and blur information is obtained, an overall evaluation of visual quality of the super-resolution image can be computed. Experimental results show that the proposed objective quality assessment method can be used in the real applications with the original high-resolution images unavailable.

목차

Abstract
 1. Introduction
 2. The Proposed Method
  2.1. SSIM Map Estimation
  2.2. Local Phase Coherence
  2.3. Quality Assessment Model
 3. Experimental Results
  3.1. Experiment I
  3.2. Experiment II
 4. Conclusion
 References

키워드

저자

• Lei Shu [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ]
• Yuming Fang [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ]
• Zhijun Fang [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China, College of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, China ]
• Yong Yang [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ]
• Fengchang Fei [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ]
• Naixue Xiong [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605