Side Information Extrapolation Using Motion-aligned Auto Regressive Model for Compressed Sensing based Wyner-Ziv Codec

• Ran Li,
• Zongliang Gan,
• Ziguan Cui,
• Minghu Wu,
• Xiuchang Zhu,

Vol. 7, No. 2, February 25, 2013
10.3837/tiis.2013.02.011, Download Paper (Free):

• Compressed sensing
• Wyner-Ziv codec
• side information
• motion-aligned auto regressive model

Abstract

In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods

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