Space-frequency quantization for wavelet image coding
Space-frequency quantization for wavelet image coding
复制标题
DOI：
10.1117/12.258247
复制
发表时间：
1996-11
期刊：
影响因子：
--
通讯作者：
Zixiang Xiong;K. Ramchandran;M. Orchard
中科院分区：
文献类型：
--
作者：
Zixiang Xiong;K. Ramchandran;M. Orchard
介绍了一种新的小波包图像编码器。该算法是在空频量化(SFQ)小波图像编码方法的基础上，对零树量化和标量量化在率失真意义上进行了联合优化。在本文中，我们将功能强大的SFQ编码范例从小波变换扩展到更一般的小波包变换。由此产生的小波包编码器通过允许联合变换和量化器设计而不假设输入图像的先验统计，在滤波器组结构的约束下提供了通用变换编码框架。换句话说，新的编码器自适应地选择适合图像的表示和适合该表示的量化。实验结果表明，对于某些图像类，我们的新编码器能够在已发表的文献中获得最好的编码性能。
A novel wavelet packet image coder is introduced in this paper. It is based on our previous work on wavelet image coding using space-frequency quantization (SFQ), in which zerotree quantization and scalar quantization are jointly optimized in a rate-distortion sense. In this paper, we extend the powerful SFQ coding paradigm from the wavelet transform to the more general wavelet packet transformation. The resulting wavelet packet coder offers a universal transform coding framework within the constraints of filter bank structures by allowing joint transform and quantizer design without assuming a priori statistics of the input image. In other words, the new coder adaptively chooses the representation to suit the image and the quantization to suit the representation. Experimental results show that, for some image classes, our new coder is capable of achieving the best coding performances among those in the published literature.