Motion-Compensated Coding and Frame-Rate Up-Conversion: Models and Analysis
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Abstract (arXiv)
Block-based motion estimation (ME) and compensation (MC) techniques are widely used in modern video processing algorithms and compression systems. The great variety of video applications and devices results in numerous compression specifications. Specifically, there is a diversity of frame-rates and bit-rates. In this paper, we study the effect of frame-rate and compression bit-rate on block-based ME and MC as commonly utilized in inter-frame coding and frame-rate up conversion (FRUC). This joint examination yields a comprehensive foundation for comparing MC procedures in coding and FRUC. First, the video signal is modeled as a noisy translational motion of an image. Then, we theoretically model the motion-compensated prediction of an available and absent frames as in coding and FRUC applications, respectively. The theoretic MC-prediction error is further analyzed and its autocorrelation function is calculated for coding and FRUC applications. We show a linear relation between the variance of the MC-prediction error and temporal-distance. While the affecting distance in MC-coding is between the predicted and reference frames, MC-FRUC is affected by the distance between the available frames used for the interpolation. Moreover, the dependency in temporal-distance implies an inverse effect of the frame-rate. FRUC performance analysis considers the prediction error variance, since it equals to the mean-squared-error of the interpolation. However, MC-coding analysis requires the entire autocorrelation function of the error; hence, analytic simplicity is beneficial. Therefore, we propose two constructions of a separable autocorrelation function for prediction error in MC-coding. We conclude by comparing our estimations with experimental results.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Apr 2014.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1.
3 papers.
- 2023Dynamic Frame Interpolation in Wavelet Domaincited by 3
- 2021Frame-rate Up-conversion Detection Based on Convolutional Neural Network for Learning Spatiotemporal Featurescited by 1
- 2022Triple Motion Estimation and Frame Interpolation based on Adaptive Threshold for Frame Rate Up-Conversioncited by 0
- 2023Dynamic Frame Interpolation in Wavelet Domain7 Sep 2023
- 2022Triple Motion Estimation and Frame Interpolation based on Adaptive Threshold for Frame Rate Up-Conversion5 Mar 2022
- 2021Frame-rate Up-conversion Detection Based on Convolutional Neural Network for Learning Spatiotemporal Features25 Mar 2021