A New Compressive Video Sensing Framework for Mobile Broadcast

Author

Chengbo Li ; Hong Jiang ; Wilford, Paul ; Yin Zhang ; Scheutzow, M.

Author_Institution

Dept. of Comput. & Appl. Math., Rice Univ., Houston, TX, USA

Volume

59

Issue

1

fYear

2013

fDate

Mar-13

Firstpage

197

Lastpage

205

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 discrete cosine transform 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.

Keywords

broadcast communication; compressed sensing; discrete cosine transforms; mobile radio; video coding; video communication; TV minimization algorithm; TVAL3; augmented Lagrangian methods; compressive sampling; compressive video sensing framework; mobile broadcast; pixelwise discrete cosine transform coefficients; reconstruction algorithm; temporal direction; total variation minimization; video coding method; video cubes; video reconstruction; Atmospheric measurements; Discrete cosine transforms; Image reconstruction; Minimization; Streaming media; TV; Video coding; Alternating minimization; augmented Lagrangian method; compressive sensing; discrete cosine transform (DCT); scalable video coding; total variation (TV); video coding;

fLanguage

English

Journal_Title

Broadcasting, IEEE Transactions on

Publisher

ieee

ISSN

0018-9316

Type

jour

DOI

10.1109/TBC.2012.2226509

Filename

6457441