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An effective hybrid video deinterlacing algorithm.

机译:一种有效的混合视频去隔行算法。

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HDTV system networks are expanding, but most TV systems still use traditional interlaced scans. In order to display the traditional TV signals on HDTV, deinterlacing and scan up conversion are applied. Even if all traditional TV systems were replaced with HDTV system, deinterlacing would be required to convert the video sequences that were originally recorded in interlaced scan to a progressive scan. Deinterlacing can improve the video quality by increasing the vertical resolution of the picture and by removing interlacing artifacts. Nowadays, the greatest challenge for deinterlacing is balancing the trade-off between implementation complexity and a reasonable image quality.;In this thesis we propose an effective hybrid deinterlacing algorithm in which a motion compensated algorithm is combined with an edge-based method based on the reliability of motion vectors. A five-field motion compensated algorithm that works by using the amount of vertical motion within the reference fields is proposed to achieve the maximum vertical resolution improvement.;A new measure for motion vector reliability assessment called reverse motion estimation (RME) is also proposed to qualify the motion vectors. The method tries reversing the calculated motion vector to confirm its validity. This measure was used in the hybrid algorithm to recognize unreliable motion vectors and switch to an edge-based method to prevent artifacts. The RME measure has a very low computational complexity compared to the other measures while being more efficient.;A Pattern-Based Directional Interpolation (PBDI) deinterlacing algorithm is introduced. The algorithm can be used in the hybrid method in the case that unreliable motion vectors are encountered. It compares three-pixel patterns in the upper and lower lines to detect twenty one edge directions and to provide clear and smooth edges with less probability chance of misleading edges. Pattern comparison is done by a combination of the sum of absolute differences and a gradient-based difference.
机译:HDTV系统网络正在扩展,但是大多数电视系统仍使用传统的隔行扫描。为了在HDTV上显示传统的电视信号,应用了隔行扫描和向上扫描转换。即使将所有传统的电视系统都替换为HDTV系统,也需要进行隔行扫描才能将隔行扫描中最初记录的视频序列转换为逐行扫描。去隔行可以通过增加图片的垂直分辨率并消除隔行伪像来提高视频质量。如今,去隔行扫描的最大挑战是在实现复杂度和合理的图像质量之间权衡取舍。在本文中,我们提出了一种有效的混合去隔行扫描算法,该算法将运动补偿算法与基于边缘的基于边缘的方法相结合。运动矢量的可靠性。提出了一种利用参考场内的垂直运动量进行工作的五场运动补偿算法,以实现最大的垂直分辨率改进。;还提出了一种用于运动矢量可靠性评估的新方法,称为反向运动估计(RME)。限定运动矢量。该方法尝试反转计算的运动矢量以确认其有效性。该措施在混合算法中用于识别不可靠的运动矢量,并切换到基于边缘的方法以防止伪影。与其他度量相比,RME度量的计算复杂度非常低,但效率更高。;引入了一种基于模式的方向插值(PBDI)去隔行算法。在遇到不可靠的运动矢量的情况下,该算法可用于混合方法。它比较上下两行中的三个像素图案,以检测21个边缘方向,并提供清晰,平滑的边缘,从而减少误导边缘的可能性。模式比较是通过绝对差之和和基于梯度的差的组合来完成的。

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