MODELING THE ENCODING TIME AND SEARCH RANGE IN DISTRIBUTED SCALABLE VIDEO CODING FOR VIDEO SENSER NETWORKS

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Abstract

Distributed scalable video coding (DSVC) has been recently gained attention due to its benefits on low encoding complexity and error resilience capability which are important in emerging video applications such as wireless video sensor networks (WVSN) and visual surveillance system (VSS). In DSVC, the side information creation plays an important role since it directly affects to the DSVC compression pereformance and complexity, notably at both encoer and decoder sides. Howevere, with many WVSN and VSS, the energy at each node is typically limited and gradually decreses along the time. In addition, the hardware components at each WVSN node is also constrained in both price and energy, causing difficulty in real time video transmission. To solve this problem, this paper proposes a complexiy control solution for SI creation in DSVC. To create SI, the computational complexity associated to the SI creation is modelled by a linear function in which linear parameters are experimentally defined. To adjust the SI complexity, a user parameter is defined based on the WVSN and VSS energy capacity. Experimental results show that the proposed complexity control solution shows benefits in overall DSVC performance, especially in both computational complexity and compression performance.