Energy-efficient image compression for resource-constrained platforms.
One of the most important goals of current and future sensor networks is energy-efficient communication of images. This paper presents a quantitative comparison between the energy costs associated with 1) direct transmission of uncompressed images and 2) sensor platform-based JPEG compression followed by transmission of the compressed image data. JPEG compression computations are mapped onto various resource-constrained platforms using a design environment that allows computation using the minimum integer and fractional bit-widths needed in view of other approximations inherent in the compression process and choice of image quality parameters. Advanced applications of JPEG, such as region of interest coding and successive/progressive transmission, are also examined. Detailed experimental results examining the tradeoffs in processor resources, processing/transmission time, bandwidth utilization, image quality, and overall energy consumption are presented.
Electrical Engineering Department, University of California, Los Angeles, CA 90095, USA. dongu@mojix.com
Dong-U
DU
Lee
Hyungjin
H
Kim
Mohammad
M
Rahimi
Deborah
D
Estrin
John D
JD
Villasenor