A Lossless Compression Algorithm for Astronomical Sequential Images Based on Hybrid Coder
Ying Wang, Qing ZHOU, Jin-wei SONG · Chinese Journal of Space Science · 2021
An image lossless compression algorithm based on time and space dimension prediction and hybrid entropy encoder is proposed. The algorithm is applied to the astronomical sequential imagery produced by fixed-point photography. The time and space dimension prediction can eliminate the time correlation and spatial correlation of astronomical sequential imagery, and the hybrid entropy encoder combined with high-entropy coding and low-entropy coding makes full use of the sparsity of the prediction error distribution. For sequential imagery, the algorithm first performs inter-frame prediction on time dimension to remove the time correlation, and then adopts histogram filtering and context prediction on spatial dimension for the residual imagery of inter-frame prediction to remove the spatial correlation. Finally, the prediction error is sent to the hybrid entropy encoder for coding. The experimental results show that the performance of the proposed algorithm is better than that of JPEG-LS, with an average compression ratio of about 15% improvement. The algorithm has simple structure and low computational complexity, which is friendly for hardware implementation and suitable for lossless compression of space astronomical imagery.