Lossless Image Compression Using Super-Spatial Structure Prediction

Digital Object Identifier 10.1109/LSP.2010.2040925We recognize that the key challenge in image compression is to efficiently represent and encode high-frequency image structure components, such as edges, patterns, and textures. In this work, we develop an efficient lossless image compression scheme called super-spatial structure prediction. This super-spatial prediction is motivated by motion prediction in video coding, attempting to find an optimal prediction of structure components within previously encoded image regions. We find that this super-spatial prediction is very efficient for image regions with significant structure components. Our extensive experimental results demonstrate that the proposed scheme is very competitive and even outperforms the state-of-the-art lossless image compression methods

Energy-Aware Portable Video Communication System Design for Wildlife Activity Monitoring

Digital Object Identifier 10.1109/MCAS.2008.923007In this paper, we introduce our recent research and development effort on energy-efficient portable video communication system design for wildlife activity monitoring. The capability of seeing what an animal sees in the field is very important for wildlife activity monitoring and research. We design an integrated video and sensor system, called DeerCam and mount it on animals so as to collect important video and sensor data about their activities in the field. From the video and sensor data collected by DeerCam, wildlife researchers will be able to extract a wealth of scientific data for studying the behavior patterns of wildlife species and understanding the dynamic of wildlife systems. We present the system architecture of DeerCam, explain our system design goals, and discuss major design issues. One of the central challenges in DeerCam system design is energy minimization. We present a new approach for energy minimization of portable video devices: power-rate-distortion (P-R-D) analysis and optimization. We discuss various approaches to minimizing the energy consumption of DeerCam, which can be also applied to other portable video devices. Results demonstrate that, by incorporating the third dimension of power consumption into conventional rate-distortion (R-D) analysis, P-R-D analysis gives us one extra dimension of flexibility in resource allocation and energy minimization and allows us to significantly reduce energy consumption.This work was supported in part by National Science Foundation under grant DBI-0529082