Arithmetic coding for image compression with adaptive weight-context classification |
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Authors: | Jiaji Wu Zhenzhen Xu Gwanggil Jeon Xiangrong Zhang Licheng Jiao |
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Affiliation: | 1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi''an 710071, China;2. Department of Embedded Systems Engineering, Incheon National University, Incheon 406-772, Republic of Korea |
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Abstract: | In this paper, a new binary arithmetic coding strategy with adaptive-weight context classification is introduced to solve the context dilution and context quantization problems for bitplane coding. In our method, the weight, obtained using a regressive–prediction algorithm, represents the degree of importance of the current coefficient/block in the wavelet transform domain. Regarding the weights as contexts, the coder reduces the context number by classifying the weights using the Lloyd–Max algorithm, such that high-order is approximated as low-order context arithmetic coding. The experimental results show that our method effectively improves the arithmetic coding performance and outperforms the compression performances of SPECK, SPIHT and JPEG2000. |
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Keywords: | Context-based arithmetic coding Adaptive Regressive–prediction Weight Context classification |
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