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

Audie Spina, A. Morales
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Abstract

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.
视频处理中对偶树离散小波变换算法的改进
本文提出了对噪声整形(NS)算法的两种改进,目的是减少对偶树离散小波变换(DDWT)中系数整形所需的处理时间。首先,子带显著系数测定(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)更有效地处理基于单个子带能量分布的变换的小波系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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