A lossless compression algorithm based on a modified Golomb code achieved a compression gain of up to 50%-60% in different contexts for multi-sensor systems.
A modified Golomb code-based lossless compression algorithm can achieve up to 50-60% compression gain for multi-sensor systems with low computational capabilities.
Effect estimate: up to 50%-60%
During the last years, multi-sensor acquisition systems have experienced a great diffusion. One of the main limiting factors is related to the huge amount of data generated within these systems and that must be carefully addressed to guarantee a certain efficiency. A solution consists in compressing data before transmission or storage. Furthermore, a lossless compression is required in monitoring applications, such as biomedical applications, where even very small signal variations can convey important information about the physical process under analysis. In this paper, we propose the lossless compression algorithm for multi-sensor systems characterized by low computational capabilities. The proposed method is based on a modified Golomb code that takes an advantage of the definition of union sets to reduce the redundancy associated to the prefix of codewords. The experimental results show that a compression gain up to 50%-60% can be achieved in different contexts.
Giada Giorgi (2019) studied this question. Lossless compression algorithm based on a modified Golomb code was evaluated on Compression gain (up to 50%-60%). A lossless compression algorithm based on a modified Golomb code achieved a compression gain of up to 50%-60% in different contexts for multi-sensor systems.