Accuracy-energy tradeoffs in digital image processing using embedded computing platforms

As more and more multimedia applications are integrated in mobile devices, a significant amount of energy is devoted to digital signal processing (DSP). Thus, reducing energy consumption for DSP systems has become an important design goal for battery operated mobile devices. Since supply voltage scaling is one of the most effective methods to reduce power/energy consumption, this study examines aggressive voltage scaling to achieve significant energy savings by allowing some output quality degradation for error tolerant image processing system. The objective of proposed research is to explore ultra-low energy image processing system design methodologies based on efficient accuracy (quality)-energy tradeoffs. This dissertation presents several new analyses and techniques to achieve significant energy savings without noticeable quality degradation under aggressive voltage scaling. In the first, this work starts from accurate error analysis and a model based on input sequence dependent delay estimation. Based on the analysis, we explain the dependence of voltage scalability on input image types, which may be used for input dependent adaptive control for optimal accuracy-energy tradeoffs. In addition, this work includes the system-level analysis of the impact of aggressive voltage scaling on overall energy consumption and a low-cost technique to reduce overall energy consumption. Lastly, this research exploits an error concealment technique to improve the efficiency of accuracy-energy tradeoffs. For an image compression system, the technique minimizes the impact of delay errors on output quality while allowing very low voltage operations for significant energy reduction.PhDCommittee Chair: Wolf, Marilyn; Committee Member: Anderson, David; Committee Member: Kim, Hyesoon; Committee Member: Mukhopadhyay, Saibal; Committee Member: Vela, Patrici