A new compressive video sensing framework for mobile broadcast
Chengbo Li, Hong Jiang, Paul Wilford, Yin Zhang, Mike, Scheutzow
TL;DR
This paper introduces a novel compressive video sensing framework that enables scalable video coding for mobile broadcast by reconstructing videos from compressive measurements using TV minimization.
Contribution
It proposes a new video coding method based on compressive sampling with a novel reconstruction algorithm derived from TVAL3, tailored for mobile broadcast applications.
Findings
Achieves scalable video coding from compressive measurements.
Uses TV minimization for effective video reconstruction.
Suitable for mobile broadcast scenarios.
Abstract
A new video coding method based on compressive sampling is proposed. In this method, a video is coded using compressive measurements on video cubes. Video reconstruction is performed by minimization of total variation (TV) of the pixelwise DCT coefficients along the temporal direction. A new reconstruction algorithm is developed from TVAL3, an efficient TV minimization algorithm based on the alternating minimization and augmented Lagrangian methods. Video coding with this method is inherently scalable, and has applications in mobile broadcast.
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