Low-complexity video coding via power–rate–distortion optimization

Wireless multimedia sensor networks (WMSNs) have been potentially applicable for several emerging applications. The resources, i.e., power and bandwidth available to visual sensors in a WMSN are, however, very limited. Hence, it is important but challenging to achieve efficient resource allocation and optimal video data compression while maximizing the overall network lifetime. In this paper, a power–rate–distortion (PRD) optimized resource-scalable low-complexity multiview video encoding scheme is proposed. In our video encoder, both the temporal and interview information can be exploited based on the comparisons of extracted media hashes without performing motion and disparity estimations, which are known to be time-consuming. We present a PRD model to characterize the relationship between the available resources and the RD performance of our encoder. More specifically, an RD function in terms of the percentages for different coding modes of blocks and the target bit rate under the available resource constraints is derived for optimal coding mode decision. The major goal here is to design a PRD model to optimize a “motion estimation-free” low-complexity video encoder for applications with resource-limited devices, instead of designing a general-purpose video codec to compete compression performance against current compression standards (e.g., H.264/AVC). Analytic results verify the accuracy of our PRD model, which can provide a theoretical guideline for performance optimization under limited resource constraints. Simulation results on joint RD performance and power consumption (measured in terms of encoding time) demonstrate the applicability of our video coding scheme for WMSNs.

► Propose a power–rate–distortion (PRD) optimized low-power video encoding scheme.
► Propose a model to describe the relationship between resource and RD performance.
► Provide a guideline for coding performance optimization under limited resources.