A context based lossless compression algorithm for ionogram data

Context modeling has recently drawn much research interest to improve the performance of a compression algorithm for binary data such as images. This is because it can help to remove the remaining statistical redundancy among the data after the prediction stage. In this paper, a simple context modelling scheme is proposed in the lossless compression of ionogram data. Experiments show that compared with the one without context modelling, this scheme can provide an over 13% increase in the average compression ratio for the sample data files with almost nothing added in the computation complexity.