基于噪声分布特性的压缩视频超分辨率重建

徐忠强; 朱秀昌

doi:10.3724/SP.J.1146.2006.01255

基于噪声分布特性的压缩视频超分辨率重建

doi: 10.3724/SP.J.1146.2006.01255

基金项目:

江苏省自然科学基金(BK2004151)资助课题

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出版历程
- 收稿日期: 2006-08-23
- 修回日期: 2007-05-17
- 刊出日期: 2008-03-19

Super-Resolution Reconstruction of Compressed Video Based on Noise Distribution Property

摘要

摘要: 该文通过对视频压缩过程进行建模，利用比特流中的量化信息和运动信息，建立了量化噪声和运动估计噪声模型，并考虑成像过程的加性噪声，总的噪声模型对不同的量化器可自适应调整。以Huber-Markov 随机场作为图像的先验模型，用梯度下降法进行MAP超分辨率重建，对其特性进行了分析。仿真实验表明，该算法重建图像的主、客观质量较高。
- 压缩视频; 超分辨率重; MAP; DCT量化噪声; 运动估计噪声
Abstract: This paper models the process of video compression, DCT quantization noise and motion estimation noise with exploiting the quantization step size and motion information embedded in the bit-stream. Together with the additive noise term of imaging, the proposed total noise term adaptively adjusts for different quantizers. With a Huber-Markov Random Field (HMRF) as the prior model, the gradient descent algorithm and MAP super-resolution reconstruction are presented and their performances are also analyzed. Simulation results show that proposed algorithm obtains better objective and subjective performances.

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参考文献(1)

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