A posteriori restoration of block transform-compressed data

Summary form only given; substantially as follows. The NASA/JPL Galileo spacecraft uses lossy data compression for the transmission of its science imagery over the low-bandwidth communication system. The technique for image compression is a block transform technique based on the integer cosine transform (ICT), a derivative of the JPEG image compression standard where a computationally efficient integer cosine transform implementation replaces JPEG´s discrete cosine transform (DCT). JPEG and ICT are examples of block transform-based compression schemes. The compression is achieved by quantizing the transformed data. The distortion characteristics of block transform-based compression techniques are understandable in terms of the properties of the transform basis functions and the transform coefficient quantization error [Boden, 1995]. For scientific applications such as Galileo, it is particularly desirable to mitigate the quantization distortion in the decompressed image to enhance science return. Galileo´s limited computational resources preclude additional processing, hence attempts at data restoration are limited to a posteriori processing. The present authors consider two known a posteriori enhancement techniques, transform coefficient adjustment [Ahumada Jr. and Horng], and low-pass filtering [Reeve III and Lim]. These techniques are adapted to ICT restoration based on a quantitative model of distortion statistics, and combined to achieve significant objective and subjective improvement in restored image fidelity compared with original data