Title of Paper: Region-of-Interest Data Compression with Prioritized Buffer Management

Principal Author: Dr. Samuel Dolinar

Abstract: We describe an integrated system for intelligent compression and transmission of copious data acquired by spaceborne instruments. Typically, imagers and remote sensors have the capability to collect far more data than can be transmitted to earth, and it is important to maximize the science value of the data returned.

At its core, our system contains a modification of a progressive image compression algorithm, ICER, that will be used on the Mars ‘03 rovers. The ICER algorithm applies a wavelet decomposition and prioritizes the compressed bit layers from the wavelet subbands so as to progressively transmit the layer that gives the largest improvement in image quality per transmitted bit. Our modified version accepts additional input priorities that reflect the relative importance of various "regions of interest" in the source data, and arranges its output packets to reflect both the input regional priorities and the wavelet bit layer priorities.

The output of the data compression module is supervised by an intelligent buffer manager that shuffles the prioritized packets from many different source images and tries to select packets for transmission that will maximize the total science value received on the ground. Just as importantly, it attempts to discard only the least valuable packets when the buffer overflows (inevitably if the average data transmission rate is lower than the average data collection rate).

Besides describing the current system, the paper analyzes various algorithms for bit allocation across regions of the source data, for optimization of the buffer control algorithm, and for efficiently compressing data features useful for establishing a prioritization feedback loop between spacecraft and ground.