基于小波变换的图像信号分解与重构  

Image signal decomposition and reconstruction based on wavelets

作　　者：冯晶晶[1] 陈文利[1] 董丹凤[2] FENG Jingjing;CHEN Wenli;DONG Danfeng(School of Intelligent Science and Information Engineering,Xi’an Peihua University,Xi’an 710125,China;The First Affiliated Hospital of Xi’an Jiaotong University,Xi’an 710061,China)

机构地区：[1]西安培华学院智能科学与信息工程学院,陕西西安710125 [2]西安交通大学第一附属医院,陕西西安710061

出　　处：《电子设计工程》2021年第16期177-180,共4页Electronic Design Engineering

基　　金：国家自然科学基金项目(82002803);陕西省教育厅专项科研计划项目(19JK0635)。

摘　　要：针对图像信号的分解与重构,采用了小波变换的方法。通过研究由尺度函数生成的多分辨分析、两尺度关系,得到小波对信号的分解算法和重构算法以及信号分解和传递的示意图。在此基础上,讨论二元张量积多分辨分析,得到利用多元小波对图像的分解算法、重构算法以及图像小波分解、小波分解数据流、小波重构数据流的结构图。采用Matlab小波工具箱,对图像信号进行分解,将图像分解为不同空间、不同频率的子图像,该算法对于信号与图像压缩比高,压缩速度快,压缩后能保持信号与图像的特征不变,而且在传递过程中抗干扰。For the decomposition and reconstruction of image signal,wavelet transform is used.The decomposition algorithm and reconstruction algorithm of the signal and the schematic diagram of signal decomposition and transmission are obtained,by studying the multi⁃resolution analysis generated by scale function and the relationship between the two scales.On this basis,the binary tensor product multi⁃resolution analysis is discussed,and the image decomposition algorithm and reconstruction algorithm using multivariate wavelet are obtained,as well as the structure diagram of image wavelet decomposition,wavelet decomposition data flow and wavelet reconstruction data flow.The wavelet toolbox of Matlab is used to decompose the image signal into sub images with different space and frequency.This algorithm has high compression ratio for signal and image,fast compression speed,and can keep the characteristics of signal and image unchanged after compression,and anti⁃interference in the process of transmission.

关 键 词：小波变换 图像信号 多尺度分析 分解与重构 

分 类 号：TN957.52[电子电信—信号与信息处理]