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Enhancements in the dual tree discrete wavelet transform algorithm for video processing

机译:用于视频处理的双树离散小波变换算法的增强

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This paper proposes two enhancements to the Noise Shaping (NS) algorithm with the intent of reducing the processing time required to shape the coefficients in the dual tree discrete wavelet transform (DDWT). First, Subband Significant Coefficient Determination (SSCD) will identify the most important coefficients while eliminating the others. A second algorithm, Energy Distribution Noise Shaping (EDNS) more efficiently processes the wavelet coefficients of the transform based on individual subband energy distributions.
机译:本文提出了对噪声整形(NS)算法的两项增强,目的是减少对偶树离散小波变换(DDWT)中的系数成形所需的处理时间。首先,子带有效系数确定(SSCD)将识别最重要的系数,同时消除其他系数。第二种算法,能量分布噪声整形(EDNS)可基于各个子带能量分布更有效地处理变换的小波系数。

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