论文标题

新的一致性检查,以快速递归重建非规范采样的视频数据

Novel Consistency Check For Fast Recursive Reconstruction Of Non-Regularly Sampled Video Data

论文作者

Grosche, Simon, Seiler, Jürgen, Kaup, André

论文摘要

四分之一采样是一种新型的传感器设计,可允许获取更高分辨率的图像,而无需增加像素的数量。当用于视频数据时,每个帧中都测量了四个像素中的一个。有效地,这导致了非规范时空的子采样。与纯粹的空间或时间亚采样相比,这可以提高重建质量,因为可以降低混叠伪影。为了快速重建具有固定蒙版的此类传感器数据,提出了频率选择性重建(FSR)的递归变体。在这里,以前帧中测量的像素被投影到当前框架中以支持其重建。这样,使用模板匹配计算帧之间的运动。由于某些运动向量可能是错误的,因此进行适当的一致性检查很重要。在本文中,我们提出了更快的一致性检查方法以及一种新颖的递归FSR,该方法使用了与文献不同的投影像素不同,并且可以处理动态掩码。总的来说,与使用固定掩码的最新递归重建方法相比,我们能够将重建质量显着提高 + 1.01 dB。与单个帧重建相比,动态面罩的平均增益约为 + 1.52 dB。同时,与文献算法相比,一致性检查的计算复杂性减少了13倍。

Quarter sampling is a novel sensor design that allows for an acquisition of higher resolution images without increasing the number of pixels. When being used for video data, one out of four pixels is measured in each frame. Effectively, this leads to a non-regular spatio-temporal sub-sampling. Compared to purely spatial or temporal sub-sampling, this allows for an increased reconstruction quality, as aliasing artifacts can be reduced. For the fast reconstruction of such sensor data with a fixed mask, recursive variant of frequency selective reconstruction (FSR) was proposed. Here, pixels measured in previous frames are projected into the current frame to support its reconstruction. In doing so, the motion between the frames is computed using template matching. Since some of the motion vectors may be erroneous, it is important to perform a proper consistency checking. In this paper, we propose faster consistency checking methods as well as a novel recursive FSR that uses the projected pixels different than in literature and can handle dynamic masks. Altogether, we are able to significantly increase the reconstruction quality by + 1.01 dB compared to the state-of-the-art recursive reconstruction method using a fixed mask. Compared to a single frame reconstruction, an average gain of about + 1.52 dB is achieved for dynamic masks. At the same time, the computational complexity of the consistency checks is reduced by a factor of 13 compared to the literature algorithm.

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