Efficient arithmetic coding for wavelet image compression
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We address efficient context modeling in arithmetic coding for wavelet image compression. Quantized highpass wavelet coefficients are first mapped into a binary source, followed by high order context modeling in arithmetic coding. A blending technique is used to combine results of context modeling of different orders into a single probability estimate. Experiments show that an arithmetic coder with efficient context modeling is capable of achieving a 10 percent bitrate saving over a zeroth order adaptive arithmetic coder in high performance wavelet image coders.