engleski

Adaptive temporal frame interpolation based on video signal spatio-temporal features

Video signal recorded using modern devices is not suitable for transmission or storage on some media. Therefore it is necessary to decrease its size during the encoding process. It can be done by decreasing spatial and/or temporal resolution. On the other hand, there is also a rapid development of video displaying devices (smart phones, tablets, laptops...) which, independently on screen size, can display high resolution video signal. Therefore it is necessary to increase spatial and/or temporal resolution of video signal during the decoding process (prior to presentation). Thus the interest for algorithms that perform spatial/temporal video upscaling is growing rapidly in last decade. In this research, firstly frames from uncompressed video signal are discarded. Then the interpolation of these discarded frames is done by using an engineering approach. Since the whole process is performed on uncompressed video, interpolation error is caused only by object motion and the content change. Theoretical and empirical models developed within this research have shown that in case of low video signal temporal activity, simple frame averaging (FA) method can achieve similar interpolation error to this of more complex motion compensated frame interpolation (MCFI), thus reducing the interpolation algorithm complexity. Analysis of the influence of the block size on the motion estimation error has shown that interpolation error is the lowest for the biggest block size (16x16 pixels). According to performed analyses, an algorithm for adaptive frame interpolation based on spatio-temporal features of the video signal is proposed. The proposed temporal upscaling algorithm is compared to the state-of-the-art temporal upscaling algorithms. The results show that the proposed algorithm is competitive to state-of- the-art temporal upscaling algorithms in terms of interpolated image/video quality, while its computational complexity is significantly lower, what is very important in a world of consumer electronics devices real-time operation.

Upscalin, g ; Spatio-temporal features, Computational complexity, Interpolated image quality

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