Suboptimal Karhunen-Loève Transform for Compression of Astronomical Images

Abstract

This paper deals with a compression of image data in astronomy applications. Astronomical images are typical with their specific properties ? high grayscale bit depth, size, noise occurrence and special processing algorithms. They belong to the class of scientific images. Their processing and compression is quite different from the classic approach to the processing of multimedia images. Database of images from BOOTES (Burst Observer and Optical Transient Exploring System) has been chosen as a source of the testing signal. BOOTES is a Czech ? Spanish robotic telescope for observing of AGN (active galactic nuclei) and optical transient of GRB (gamma ray bursts) searching. There is discussed an approach based on analysis of statistical properties of image data in this paper. Eigen-images of the covariance matrix can be used as base vectors of the integral transform known as the Karhunen-Loeve (KLT). This transform minimize deviation from MSE (mean square error) point of view. The main disadvantage of KLT is its signal dependency and consequently necessity to transfer base vectors with coded data. There is described the suboptimal solution of this problem in this paper. The data distortion of lossy suboptimal Karhunen ? Loeve transform is measured by standard algorithms (e.g. MSE), the impact to the precision of data processing (e.g. object position) and subjective methods also.