Context-based entropy coding in AVS video coding standard
Image Communication
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Context modeling based on context quantization with application in wavelet image coding
IEEE Transactions on Image Processing
Mutual information-based analysis of JPEG2000 contexts
IEEE Transactions on Image Processing
Context quantization by kernel Fisher discriminant
IEEE Transactions on Image Processing
Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard
IEEE Transactions on Circuits and Systems for Video Technology
Efficient, low-complexity image coding with a set-partitioning embedded block coder
IEEE Transactions on Circuits and Systems for Video Technology
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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.