图像边缘块的CVQ分类使用SD滤波器

J. Farison, M. Quweider
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引用次数: 0

摘要

提出了一种新的图像边缘块分类方法。它是基于定义一组与边类一对一关联的线性无关的签名向量。然后设计了一组滤波向量,强调一个特征向量的投影,抑制所有其他特征向量。输入边缘块的分类是通过选择具有最大输出幅度的滤波器的指数来完成的。基于这种分类的编码图像可以保持其质量,并且比两种现有方法获得相当大的dB增益。新技术可以很容易地使用并行算法实现,并且存储需求很小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image edge block classification for CVQ using the SD filter
A novel technique to classify image edge blocks is presented. It is based on defining a set of linearly independent signature vectors with a one to one association with the edge classes. A set of filter vectors emphasizing the projection of one signature vector and suppressing all others is then designed. Classification of an input edge block is accomplished by choosing the index of the filter with the maximum output magnitude. Coded images based on this classification are shown to preserve their quality and enjoy considerable dB gain over two existing methods. The new technique can be easily implemented using a parallel algorithm with little storage requirement.
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