Reversible symmetric non-expansive convolution: An effective image boundary processing for M-channel lifting-based linear-phase filter banks
Reversible symmetric non-expansive convolution: An effective image boundary processing for M-channel lifting-based linear-phase filter banks
复制标题
可逆对称非扩张卷积：基于M通道提升的线性相位滤波器组的有效图像边界处理
DOI：
10.1109/tip.2014.2312647
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Taizo Suzuki and Masaaki Ikehara
中科院分区：
文献类型：
--
作者：
Taizo Suzuki and Hiroyuki Kudo;Taizo Suzuki and Masaaki Ikehara
本文提出了一种有效的基于提升的线性相位滤波器组的图像边界处理方法，该方法适用于统一的有损和无损图像压缩（编码），即有损到无损图像编码。我们提出的可逆对称扩展是通过操纵图像边界上的构建块和重新唤醒由于每个提升步骤上的舍入误差而丢失的每个构建块的对称性来实现的。此外，通过扩展非扩展卷积（称为可逆对称非扩展卷积）来降低复杂性，因为输入信号的数量甚至不会暂时增加。我们的方法不仅实现了可逆的边界处理，但在有损图像编码中与不可逆对称扩展相媲美，并且在有损到无损图像编码中优于周期性扩展。
We present an effective image boundary processing for-channel $(M\in\BBN, M\geq 2)$ lifting-based linear-phase filter banks that are applied to unified lossy and lossless image compression (coding), i.e., lossy-to-lossless image coding. The reversible symmetric extension we propose is achieved by manipulating building blocks on the image boundary and reawakening the symmetry of each building block that has been lost due to rounding error on each lifting step. In addition, complexity is reduced by extending nonexpansive convolution, called reversible symmetric nonexpansive convolution, because the number of input signals does not even temporarily increase. Our method not only achieves reversible boundary processing, but also is comparable with irreversible symmetric extension in lossy image coding and outperformed periodic extension in lossy-to-lossless image coding.