A New Super-resolution Reconstruction Method Combining Narrow Quantization Constraint Set and Motion Estimation for H.264 Compressed Video

D. Hu, Yingxue Zhao, P. Xiao
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Abstract

Super-resolution (SR) reconstruction technique is mainly a task of reconstructing high resolution images from a sequence of low resolution images. The super-resolution technique for H.264 compressed video has been focused by many researchers recently. This paper briefly analyzes the narrow quantization constraint set method (NQCS), and then, in consideration of motion characteristic information of H.264 compressed video, proposes a new SR reconstruction method which combines NQCS with motion characteristic information, which are spatial domain motion estimation and frequency domain motion noise respectively. Experimental results of different standard test sequences compressed by H.264 are given. The simulation shows that both the NQCS+Mnoise method which combines NQCS with frequency domain motion noise, and the NQCS+M method which combines NQCS with spatial domain motion estimation, can get higher PNSR value than NQCS. Moreover, the NQCS+M method has better performance than NQCS+Mnoise method, and our proposed method is suitable for the SR reconstruction of H.264 compressed video.
一种结合窄量化约束集和运动估计的H.264压缩视频超分辨率重建新方法
超分辨率重建技术主要是一种从一系列低分辨率图像中重建高分辨率图像的技术。H.264压缩视频的超分辨率技术是近年来研究人员关注的热点。本文简要分析了窄量化约束集方法(NQCS),在此基础上,结合H.264压缩视频的运动特征信息,提出了一种将NQCS与运动特征信息(分别为空间域运动估计和频域运动噪声)相结合的SR重构方法。给出了H.264压缩不同标准测试序列的实验结果。仿真结果表明,将NQCS与频域运动噪声相结合的NQCS+Mnoise方法和将NQCS与空域运动估计相结合的NQCS+M方法均能获得比NQCS更高的PNSR值。此外,NQCS+M方法比NQCS+Mnoise方法具有更好的性能,适用于H.264压缩视频的SR重构。
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