Abstract
The improvement of resolution of digital video requires a continuous increase of computation invested into Frame Rate Up-Conversion (FRUC). In this paper, we combine the advantages of Edge-Preserved Filtering (EPF) and Bidirectional Motion Estimation (BME) in an attempt to reduce the computational complexity. The inaccuracy of BME results from the existing similar structures in the texture regions, which can be avoided by using EPF to remove the texture details of video frames. EPF filters out by the high-frequency components, so each video frame can be subsampled before BME, at the same time, with the least accuracy degradation. EPF also preserves the edges, which prevents the deformation of object in the process of subsampling. Besides, we use predictive search to reduce the redundant search points according to the local smoothness of Motion Vector Field (MVF) to speed up BME. The experimental results show that the proposed FRUC algorithm brings good objective and subjective qualities of the interpolated frames with a low computational complexity.
Highlights
As a fundamental technique for improving the visual quality of video sequence, it is often used to prevent the degradation of quality that results from hardware or software limitations in some applications, e.g., low bit-rate video coding [2], Liquid Crystal Display (LCD) [3]
The interpolated results by the proposed algorithm are compared with those that are generated by the traditional Frame Rate Up-Conversion (FRUC) algorithms, including Bidirectional Motion Estimation (BME) [13], EBME [14], and DS-Motion Estimation (ME) [15]
Structural SIMilarity (SSIM) is a perceptual metric that is based on visible structure, and it is closer to human perception than Peak Signal-to-Noise Ratio (PSNR)
Summary
Frame Rate Up-Conversion (FRUC) is used to improve the frame rate of video sequence by periodically interpolating some frames between original frames [1]. The visual quality of an interpolated frame depends heavily on the accuracy of ME algorithm used, so lots of works [4,5,6]. A classic way is to subsample each frame before ME, but the subsampling destroys some key details in a video frame, especially edge details, which results in some degradation of ME accuracy while reducing computation. In view of this defect, Electronics 2020, 9, 156; doi:10.3390/electronics9010156 www.mdpi.com/journal/electronics. Electronics 2020, 9, 156 the objective of this paper is to design an edge-preserved subsampling and, by associating it with a rapid ME strategy, to construct a low-complex FRUC
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