链接傅里叶和PCA方法的图像查找

2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2016-09-01 DOI:10.1109/SYNASC.2016.028

Daniel Lichtblau

{"title":"链接傅里叶和PCA方法的图像查找","authors":"Daniel Lichtblau","doi":"10.1109/SYNASC.2016.028","DOIUrl":null,"url":null,"abstract":"We show a simple, yet effective, method for storing images, such that retrieval of nearby images is both fast and accurate. The main ingredients are discrete Fourier transforms to extract low frequency components, principal components analysis (PCA) for further compression, and storage in k-D trees. We illustrate the quality of results on the MNIST digit suite and also apply it to chromosome segments.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Linking Fourier and PCA Methods for Image Look-Up\",\"authors\":\"Daniel Lichtblau\",\"doi\":\"10.1109/SYNASC.2016.028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We show a simple, yet effective, method for storing images, such that retrieval of nearby images is both fast and accurate. The main ingredients are discrete Fourier transforms to extract low frequency components, principal components analysis (PCA) for further compression, and storage in k-D trees. We illustrate the quality of results on the MNIST digit suite and also apply it to chromosome segments.\",\"PeriodicalId\":268635,\"journal\":{\"name\":\"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC.2016.028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2016.028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 5

摘要

我们展示了一种简单而有效的图像存储方法，使得附近图像的检索既快速又准确。主要成分是离散傅里叶变换提取低频成分，主成分分析(PCA)进一步压缩，并存储在k-D树。我们说明了MNIST数字套件结果的质量，并将其应用于染色体片段。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Linking Fourier and PCA Methods for Image Look-Up

We show a simple, yet effective, method for storing images, such that retrieval of nearby images is both fast and accurate. The main ingredients are discrete Fourier transforms to extract low frequency components, principal components analysis (PCA) for further compression, and storage in k-D trees. We illustrate the quality of results on the MNIST digit suite and also apply it to chromosome segments.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

自引率

0.00%

发文量