计算机工程与应用2012，Vol.48Issue(6)：181-184,4.DOI:10.3778/j.issn.1002-8331.2012.06.052
压缩视频的正则化投影超分辨率重建
Compressed video super-resolution reconstruction based on regularization and projection to convex set
曾强宇 1何小海 1陈为龙1
作者信息
- 1. 四川大学电子信息学院图像信息研究所,成都610064
- 折叠
摘要
Abstract
Compressed video Super-Resolution(SR) technique estimates High-Resolution(HR) images from a sequence of Low-Resolu-tion( LR) observations, it has been a great focus for video SR. Based on the theory of regularization and projection to a convex set, a novel SR algorithm is developed and analyzed using the quantization information from the compressed bitstream. The regularized cost function using the temporal and spatial prior information is proposed. The iterative gradient descent algorithm is utilized to reconstruct the HR image. The reconstructed HR image projects to a convex set in the DCT domain. Experimental results demonstrate that the proposed algorithm has an improvement in terms of both objective and subjective quality, and it is applicable for compressed images.关键词
正则化/凸集投影/超分辨率重建/压缩视频Key words
regularization/projection to a convex set/super-resolution reconstruction/compressed video分类
信息技术与安全科学引用本文复制引用
曾强宇,何小海,陈为龙..压缩视频的正则化投影超分辨率重建[J].计算机工程与应用,2012,48(6):181-184,4.
