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Super-Resolution Reconstruction of Compressed Video Based on Noise Distribution Property |
Xu Zhong-qiang;Zhu Xiu-chang |
Information Industry Ministry and Jiangsu Province Key Lab of Image Processing & Image Communication, Nanjing University of Posts & Telecommunications, Nanjing 210003, China |
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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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Received: 23 August 2006
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