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An Improved Huber-MAP Post Filtering Method for DCT-based Compressed Video Sequences

机译:基于DCT的压缩视频序列的改进的Huber-Map后滤波方法

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Maximum a posteriori (MAP) post processing is widely investigated to reduce digital video or image coding artifacts. Many MAP post-filtering methods have adopted the Huber-Markov random field (HMRF) as a prior probability model. However, a drawback of the Huber-MAP post-filter is that it blurs image structures and details in video sequences when removing coding artifacts, such as blocking and ringing. This paper proposed an improved prior model to preserve edge information in images of video sequences as well as to reduce coding artifacts. Experimental results show the performance improvements of the proposed approach over the Huber-MAP post-filter. The performance of the proposed approach is also comparable to that of the H.264 post-filter, in terms of the peak signal to noise ratio (PSNR) and the visual picture quality.
机译:广泛研究了最大后验(地图)后处理以减少数字视频或图像编码伪像。许多地图后过滤方法已采用Huber-Markov随机字段(HMRF)作为先前概率模型。然而,返回后滤波器的缺点是在去除编码伪像时,它在视频序列中的图像结构和细节模糊,例如阻塞和振铃。本文提出了一种改进的先前模型,以保护视频序列图像中的边缘信息以及减少编码伪像。实验结果表明,在过滤器后普通地图上提出的方法的性能改进。所提出的方法的性能也与滤光比(PSNR)的峰值信号和视觉图像质量方面的过滤后的H.264的性能相当。

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