Adaptive-distributed arithmetic coding for lossless compression
Jiaji Wu, Minli Wang, Jechang Jeong, Licheng Jiao
Abstract
Jiaji Wu, Minli Wang, Jechang Jeong, Licheng Jiao
Abstract
Distributed arithmetic coding (DAC) is an effective implementation of Slepian-Wolf coding (SWC), especially for short data blocks. However, currently, most of the DAC research methods focus on the lossy compression on the condition that the prior knowledge is known in advance. In order to realize lossless and adaptive compression, in this paper, we propose lossless adaptive-distributed arithmetic coding (LADAC) using the method of EOF (end of the file) and the adaptive encoding. In our proposed LADAC, encoder and decoder can work simultaneously instead of alternatively, and encoder-driven method is also achieved without a feedback channel instead of decoder-driven. Experimental results show that LADAC performs the better compression performance and the lower complexity than conventional lossless distributed arithmetic coding (LDAC).
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Distributed arithmetic coding (DAC) is an effective implementation of Slepian-Wolf coding (SWC), especially for short data blocks. However, currently, most of the DAC research methods focus on the lossy compression on the condition that the prior knowledge is known in advance. In order to realize lossless and adaptive compression, in this paper, we propose lossless adaptive-distributed arithmetic coding (LADAC) using the method of EOF (end of the file) and the adaptive encoding. In our proposed LADAC, encoder and decoder can work simultaneously instead of alternatively, and encoder-driven method is also achieved without a feedback channel instead of decoder-driven. Experimental results show that LADAC performs the better compression performance and the lower complexity than conventional lossless distributed arithmetic coding (LDAC).
Key concepts: Lossless compression, Adaptive coding, Context-adaptive binary arithmetic coding, Lossy compression, Arithmetic coding, Computer science, Encoder, Entropy encoding