IEEE Trans Image Process. 2016 Apr;25(4):1544-55. doi: 10.1109/TIP.2016.2523344. Epub 2016 Jan 28.
Super resolution (SR) for real-life video sequences is a challenging problem due to complex nature of the motion fields. In this paper, a novel blind SR method is proposed to improve the spatial resolution of video sequences, while the overall point spread function of the imaging system, motion fields, and noise statistics are unknown. To estimate the blur(s), first, a nonuniform interpolation SR method is utilized to upsample the frames, and then, the blur(s) is(are) estimated through a multi-scale process. The blur estimation process is initially performed on a few emphasized edges and gradually on more edges as the iterations continue. Also for faster convergence, the blur is estimated in the filter domain rather than the pixel domain. The high-resolution frames are estimated using a cost function that has the fidelity and regularization terms of type Huber-Markov random field to preserve edges and fine details. The fidelity term is adaptively weighted at each iteration using a masking operation to suppress artifacts due to inaccurate motions. Very promising results are obtained for real-life videos containing detailed structures, complex motions, fast-moving objects, deformable regions, or severe brightness changes. The proposed method outperforms the state of the art in all performed experiments through both subjective and objective evaluations. The results are available online at http://lyle.smu.edu/~rajand/Video_SR/.
由于运动场的复杂性，真实视频序列的超分辨率（SR）是一个具有挑战性的问题。在本文中，提出了一种新的盲 SR 方法，以提高视频序列的空间分辨率，而成像系统、运动场和噪声统计的整体点扩展函数未知。为了估计模糊(s)，首先利用非均匀插值 SR 方法对帧进行上采样，然后通过多尺度处理估计模糊(s)。模糊估计过程最初在少数强调边缘上进行，并随着迭代的继续逐渐在更多边缘上进行。此外，为了更快地收敛，模糊估计是在滤波器域而不是像素域中进行的。使用具有 Huber-Markov 随机场保真度和正则化项的代价函数来估计高分辨率帧，以保持边缘和细微细节。在每个迭代中，使用掩蔽操作自适应地加权保真度项，以抑制由于运动不准确而产生的伪影。对于包含详细结构、复杂运动、快速移动物体、可变形区域或严重亮度变化的真实视频，得到了非常有前景的结果。通过主观和客观评估，在所有进行的实验中，所提出的方法都优于现有技术。结果可在 http://lyle.smu.edu/~rajand/Video_SR/ 上获得。
