Research of Super-Resolution Image Reconstruction Methods

2014 ◽  
Vol 687-691 ◽  
pp. 3782-3786
Author(s):  
Ling Tang
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Image Reconstruction ◽  
Development Process ◽  
Super Resolution ◽  
Resolution Image ◽  
Reconstruction Methods ◽  
Research Findings

The super-resolution image reconstruction has become a hot topic in the areas of image processing and computer vision because of its extensive theoretical and practical values. This paper described the concept of super-resolution reconstruction, reviewed the development process of the technique, common algorithms classification, the current research findings and other related issues. The characteristics of different algorithms are also analyzed.

Survey of Super-resolution Image Reconstruction Methods

2014 ◽  
Vol 39 (8) ◽  
pp. 1202-1213 ◽  
Author(s):  
Heng SU ◽  
Jie ZHOU ◽  
Zhi-Hao ZHANG
Keyword(s):  
Image Reconstruction ◽  
Super Resolution ◽  
Resolution Image ◽  
Reconstruction Methods

scholarly journals Alternating Direction Projections onto Convex Sets for Super-Resolution Image Reconstruction

2020 ◽  
Vol 49 (1) ◽  
pp. 179-190
Author(s):  
Bin Zhou ◽  
Dong-jun Ye ◽  
Wei Wei ◽  
Marcin Wozniak
Keyword(s):  
Computer Vision ◽  
Image Reconstruction ◽  
Numerical Experiments ◽  
Convex Sets ◽  
Super Resolution ◽  
Experimental Results ◽  
Gradient Field ◽  
Resolution Image ◽  
Alternating Direction ◽  
Proposed Model

Image reconstruction is important in computer vision and many technologies have been presented to achieve better results. In this paper, gradient information is introduced to define new convex sets. A novel POCS-based model is proposed for super resolution reconstruction. The projection on the convex sets is alternative according to the gray value field and the gradient field. Then the local noise estimation is introduced to determine the threshold adaptively. The efficiency of our proposed model is verified by several numerical experiments. Experimental results show that, the PSNR and the SSIM can be both significantly improved by the proposed model.

Fast MAP-based multiframe super-resolution image reconstruction

2005 ◽  
Vol 23 (7) ◽  
pp. 671-679 ◽  
Author(s):  
Di Zhang ◽  
Huifang Li ◽  
Minghui Du
Keyword(s):  
Image Reconstruction ◽  
Super Resolution ◽  
Resolution Image

A soft MAP framework for blind super-resolution image reconstruction

2009 ◽  
Vol 27 (4) ◽  
pp. 364-373 ◽  
Author(s):  
Yu He ◽  
Kim-Hui Yap ◽  
Li Chen ◽  
Lap-Pui Chau
Keyword(s):  
Image Reconstruction ◽  
Super Resolution ◽  
Resolution Image
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