context-based adaptive arithmetic coding (CAAC) has high coding efficiency and is adopted by the majority of advanced compression algorithms. In this paper, five new techniques are proposed to further improve the perf...
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context-based adaptive arithmetic coding (CAAC) has high coding efficiency and is adopted by the majority of advanced compression algorithms. In this paper, five new techniques are proposed to further improve the performance of CAAC. They make the frequency table (the table used to estimate the probability distribution of data according to the past input) of CAAC converge to the true probability distribution rapidly and hence improve the coding efficiency. Instead of varying only one entry of the frequency table, the proposed range-adjusting scheme adjusts the entries near to the current input value together. With the proposed mutual-learning scheme, the frequency tables of the contexts highly correlated to the current context are also adjusted. The proposed increasingly adjusting step scheme applies a greater adjusting step for recent data. The proposed adaptive initialization scheme uses a proper model to initialize the frequency table. Moreover, a local frequency table is generated according to local information. We perform several simulations on edge-directed prediction-based lossless image compression, coefficient encoding in JPEG, bit plane coding in JPEG 2000, and motion vector residue coding in video compression. All simulations confirm that the proposed techniques can reduce the bit rate and are beneficial for data compression.
The increasing use of three-dimensional imaging modalities triggers the need for efficient techniques to transport and store the related volumetric data. Desired properties like quality and resolution scalability, reg...
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ISBN:
(纸本)0819437603
The increasing use of three-dimensional imaging modalities triggers the need for efficient techniques to transport and store the related volumetric data. Desired properties like quality and resolution scalability, region-of-interest coding, lossy-to-lossless coding and excellent rate-distortion characteristics for as well low as high bit-rates are inherently supported by wavelet-based compression tools. In this paper a new 3D wavelet-based compression engine is proposed and compared against a classical 3D JPEG-based coder and a state-of-the-art 3D SPIHT coder for different medical imaging modalities. Furthermore, we evaluate the performance of a selected set of lossless integer lifting kernels. We demonstrate that the performance of the proposed coder is superior for lossless coding, and competitive with 3D SPIHT at lower bit-rates.
A novel compression algorithm for weather radar data based on integer wavelet transforms and zerotree coding is presented, Considering the dependencies of the radar data, we give an efficient pre-processing of the dat...
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ISBN:
(纸本)0819442798
A novel compression algorithm for weather radar data based on integer wavelet transforms and zerotree coding is presented, Considering the dependencies of the radar data, we give an efficient pre-processing of the data first. Then an advanced Embedded Zerotree Wavelet encoding algorithm is presented which uses context-based adaptive arithmetic coding to improve its performance. Experimental results show that the compression ratios are improved significantly both for lossless and lossy data compression.
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