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An inpainting-based deinterlacing method

机译:一种基于修复的去隔行方法

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摘要

Video is usually acquired in interlaced format, where each image frame is composed of two image fields, each field/nholding same parity lines. However, many display devices require progressive video as input; also, many video processing tasks perform better on progressive material than on interlaced video. In the literature, there exist a great number of algorithms for interlaced to progressive video conversion, with a great tradeoff between the speed and quality of the results. The best algorithms in terms of image quality require motion compensation; hence, they are computationally very intensive. In this paper, we propose a novel deinterlacing algorithm based on ideas from the image inpainting arena. We view the lines to interpolate as gaps that we need to inpaint. Numerically, this is implemented using a dynamic programming procedure, which ensures a complexity of O(S), where S is the number of pixels in the image. The results obtained with our algorithm compare favorably, in terms of image quality, with state-of-the-art methods, but at a lower computational cost, since we do not need to perform motion field estimation.
机译:视频通常以隔行格式获取,其中每个图像帧由两个图像场组成,每个场/保持相同的奇偶校验线。但是,许多显示设备需要渐进视频作为输入。同样,许多视频处理任务在逐行扫描素材上的性能要优于隔行视频。在文献中,存在大量用于隔行到逐行视频转换的算法,并且在结果的速度和质量之间有很大的权衡。就图像质量而言,最好的算法需要运动补偿。因此,它们在计算上非常密集。在本文中,我们根据图像修复领域的想法提出了一种新颖的去隔行算法。我们将要插入的线视为需要修补的间隙。从数字上讲,这是使用动态编程过程实现的,该过程可确保O(S)的复杂度,其中S是图像中的像素数。使用我们的算法获得的结果在图像质量方面可以与最新技术相媲美,但是计算成本较低,因为我们不需要执行运动场估计。

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