An Improved EZW Image Coding Method Based on Lifting Wavelet

Guowei, Tang; Feng, Qi; Li, Jinghui

doi:10.1109/wicom.2007.719

Cited by 1 publication

(3 citation statements)

References 8 publications

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“…It is clear that the above two equations satisfy conditions given by (8). Moreover, (9) implies that, like quincunx filters obtained by the method introduced in subsection 2.2, the two lifting operators P and U are symmetrical.…”

Section: The Prediction and Update Operatorsmentioning

confidence: 92%

“…Considering the characteristics of transformed coefficients and in order to refine quantization, a novel scheme of taking quantization threshold is proposed in [9], which replaces the power of 2 with the square of integer. The latter scheme can shorten the differential value between higher quantization thresholds.…”

Section: Quantization Threshold For Quincunx Liftingmentioning

confidence: 99%

“…Considering the characteristics of transformed coefficients, the square of integer is taken as quantization threshold proposed in [9], instead of the power of 2 as quantization threshold used in traditional zerotree wavelet coding. In view of compression rate (CR) and the quality of reconstructed images, we adopt both schemes of taking quantization threshold in image coding based on quincunx lifting.…”

Section: Introductionmentioning

confidence: 99%

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Embedded Zerotree Wavelet Based Image Coding via Quincunx Lifting

Lü

Zhan

2008

2008 Congress on Image and Signal Processing

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This paper proposes a simple and symmetrical scheme for the prediction and update operators in quincunx lifting, which is then applied into image coding based on Embedded Zerotree Wavelet (EZW) algorithm. In addition, we present a new strategy for taking quantization threshold by combining the power of 2 with the square of integer. The former is used for image coding at higher bit rates and the latter at lower bit rates. The experimental results demonstrate that the proposed method can improve the quality of the reconstructed image.

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Section: The Prediction and Update Operatorsmentioning

confidence: 92%

Section: Quantization Threshold For Quincunx Liftingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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