{"title":"Construction of an orthonormal complex multiresolution analysis","authors":"Liying Wei, T. Blu","doi":"10.1109/ICASSP.2013.6638081","DOIUrl":null,"url":null,"abstract":"We design two complex filters {h[n], g[n])} for an orthogonal filter bank structure based on two atom functions {ρ<sub>0</sub><sup>α</sup>(t), ρ<sub>1/2</sub><sup>α</sup>(t)}, such that: 1) they generate an orthonormal multiwavelet basis; 2) the two complex conjugate wavelets are Hilbert wavelets, i.e., their frequency responses are supported either on positive or negative frequencies; and 3) the two scaling functions are real. The developed complex wavelet transform (CWT) is non-redundant, nearly shift-invariant, and distinguishable for diagonal features. The distinguishability in diagonal features is demonstrated by comparison with real discrete wavelet transform.","PeriodicalId":183968,"journal":{"name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2013.6638081","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We design two complex filters {h[n], g[n])} for an orthogonal filter bank structure based on two atom functions {ρ0α(t), ρ1/2α(t)}, such that: 1) they generate an orthonormal multiwavelet basis; 2) the two complex conjugate wavelets are Hilbert wavelets, i.e., their frequency responses are supported either on positive or negative frequencies; and 3) the two scaling functions are real. The developed complex wavelet transform (CWT) is non-redundant, nearly shift-invariant, and distinguishable for diagonal features. The distinguishability in diagonal features is demonstrated by comparison with real discrete wavelet transform.