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Pixel Club: Spatio-Temporal Bit-Allocation for Low Bit-Rate Video Coding
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Yehuda Dar (EE, Technion)
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Tuesday, 9.7.2013, 13:30
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Taub 401
The digital video is a 3D spatio-temporal signal formed as a sequence of 2D images (frames) captured over time. Hence, a sampled video represents a large amount of information. As a result, video transmission and storage systems require efficient coding and should be analyzed from a rate-distortion perspective. Specifically, good quality video coding for low bit-rate applications has great importance for transmission over narrow-bandwidth channels and for storage with limited memory capacity. Improvement of low bit-rate video compression by temporal-scaling appears in the literature in the form of frame-skipping mechanisms. However, no theoretic explanation was given for the complete compression and frame-skipping system. Moreover, frame-skipping methods usually require modifications in the original codec.

Previous studies showed, theoretically and experimentally, the benefits of spatial scaling for coding of image and video signals at low bit-rates. In this work, we expand a previous analysis for image compression and adapt it to video signals. Down-scaling in the spatial and temporal dimensions is examined. We show, both analytically and experimentally, that at low bit-rates, we benefit from applying spatio-temporal scaling. The proposed method includes down-scaling before the compression and a corresponding up-scaling afterwards, while the codec itself is left unmodified. We propose analytic models for low bit-rate compression and frame-rate up conversion (FRUC). Specifically, we theoretically model the motion-compensated prediction of an available and absent frames as in coding and frame-rate up-conversion (FRUC) applications, respectively. The model is designed for multi-resolution analysis.

In addition, we formulate a bit-allocation procedure and propose a method for finding the optimal down-scaling factors of a given video by its second-order statistics and a bit-budget. We validate our model with experimental results of H.264 compression.

M.Sc. research under the supervision of prof. Alfred M. Bruckstein
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