摘要
提出了一种基于五株采样的提升算法 ,实现了一分为二的分解与重构。通过此算法可以构造非线性的形态小波变换 ,保持图像的几何信息。
This paper presents a bi-graph image decomposition based on quincunx sampling lifting scheme, which decomposes an original image to a lower-resolution one and a different one between the original image and the lower-resolution image. The proposed scheme is of low-complexity and need not allocate additional memory.This paper introduces some simple examples, such as linear mean-lifting, nonlinear max-lifting and min-lifting. Mean-lifting is good at erasing redundant data, and max-lifting or min-lifting can effectively preserve important geometric information.
出处
《武汉大学学报(信息科学版)》
EI
CSCD
北大核心
2004年第7期628-631,634,共5页
Geomatics and Information Science of Wuhan University
基金
武汉大学知识创新工程基金资助项目 ( 90 42 70 0 72 )
关键词
五株采样
提升算法
小波变换
形态小波变换
quincunx sampling
lifting scheme
wavelet transform
morphological wavelet