{"title":"Parametric estimation of multi-line parameters based on slide algorithm","authors":"S. Djukanović, M. Simeunović, I. Djurović","doi":"10.5281/ZENODO.44206","DOIUrl":null,"url":null,"abstract":"The subspace-based line detection (SLIDE) algorithm enables the estimation of parameters of multiple lines within a digital image by mapping these lines to frequency modulated (FM) signals. In this paper, we consider the estimation of such obtained FM signals by using estimators developed for polynomial-phase signals (PPSs). For this purpose, a recently proposed method that combines the cubic phase function (CPF) and high-order ambiguity function (HAF), referred to as the product CPF-HAF (PCPF-HAF), has been used. Simulations show that the PCPF-HAF-based estimator is more accurate than the estimators based on time-frequency representations.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 22nd European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.44206","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
The subspace-based line detection (SLIDE) algorithm enables the estimation of parameters of multiple lines within a digital image by mapping these lines to frequency modulated (FM) signals. In this paper, we consider the estimation of such obtained FM signals by using estimators developed for polynomial-phase signals (PPSs). For this purpose, a recently proposed method that combines the cubic phase function (CPF) and high-order ambiguity function (HAF), referred to as the product CPF-HAF (PCPF-HAF), has been used. Simulations show that the PCPF-HAF-based estimator is more accurate than the estimators based on time-frequency representations.