摘要
为利用低分辨率压缩图像序列来重建高分辨率图像序列,提出一种在凸集投影(POCS)方法框架下基于整数DCT域量化噪声模型的针对H.264标准压缩视频的超分辨率重建方法.首先建立压缩视频的降质退化模型,然后根据H.264标准中的整数DCT变换和量化过程建立整数DCT域的量化噪声模型,最后在凸集投影算法的框架下给出了基于整数DCT域量化噪声的超分辨率重建算法.实验表明该算法的超分辨率重建结果的主观质量提高明显,峰值信噪比可达到30dB,一般迭代5次即可得到良好结果,算法复杂度较低.
To reconstruct high-resolution（HR） images from a sequence of low-resolution（LR） compressed images,this paper proposes a novel algorithm focused on super-resolution reconstruction of H.264 compressed video,which is based on the integer DCT transform-domain quantization noise.Firstly,models of compressed video and integer DCT transform-domain quantization noise are surveyed.Then the reconstruction algorithm under the POCS theory is proposed.Experimental results demonstrate that this algorithm has a great improvement in subjective visual quality and low computation complexity,in which PSNR can reach 30 dB and iterations are less than 5 times.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2010年第5期721-726,共6页
Journal of Harbin Institute of Technology
基金
黑龙江省自然科学基金资助项目(ZJG04-0701)
