CCA Performance of a New Source List/EZW Hybrid Compression Algorithm

摘要

A new data compression algorithm for encoding astronomical source lists is presented. Two experiments in combined compression and analysis (CCA) are described, the first using simulated imagery based upon a tractable source list model, and the second using images from SPIRIT III, a spaceborne infrared sensor. A CCA system consisting of the source list compressor followed by a zerotree-wavelet residual encoder is compared to alternatives based on three other astronomical image compression algorithms. CCA performance is expressed in terms of image distortion along with relevant measures of point source detection and estimation quality. Some variations of performance with compression bit rate and point source flux are characterized. While most of the compression algorithms reduce high-frequency quantum noise at certain bit rates, conclusive evidence is not found that such denoising brings an improvement in point source detection or estimation performance of the CCA systems. The proposed algorithm is a top performer in every measure of CCA performance; the computational complexity is relatively high, however.