Influence of lossy compression techniques on processing precision of astronomical images

Compression of image data from Burst Observer and Optical Transient Exploring System (BOOTES) is discussed. BOOTES project is an international robotic telescope for optical transient of gamma ray bursts (GRB). The statistical distribution of image functions in astronomical images from wide field and deep sky cameras is compared with Gaussian and Laplacean probability density function (pdj). The comparison of two irrelevancy reduction methods is presented from a scientific (astrometry and photometry) point of view. First one is based on a statistical approach to data compression and it is suggested from the Karhunen-Loeve transform (KLT) with uniform quantization in spectral domain. Second technique is derived from wavelet decomposition with adaptive choosing of used mother wavelet