{"title":"点对象识别。一些单通道和多通道应用","authors":"Peter Linde, Ralph Snel, Stefan Spännare","doi":"10.1016/S0083-6656(97)00047-0","DOIUrl":null,"url":null,"abstract":"<div><p>High-precision photometric analysis of images of crowded stellar fields needs sophisticated algorithms. The photometric precision is, however, a strong function of the completeness of source detection. We discuss several aspects of this problem, both with relation to single- and multi-channel applications. In single images, we separate detection into two phases, source image enhancement and actual detection. Comparative tests show a point spread function pixel fitting technique to give the best results. For the fraction of undetectable stars still affecting image statistics, we have developed a technique to extract information about their effect on the faint-end luminosity function. We give two examples of multi-channel image fusion applications: (1) a combination of low- and high-resolution images and (2) removal of undersampling effects by sub-pixel image displacements. Preliminary results show considerable potential for these techniques.</p></div>","PeriodicalId":101275,"journal":{"name":"Vistas in Astronomy","volume":"41 3","pages":"Pages 419-426"},"PeriodicalIF":0.0000,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0083-6656(97)00047-0","citationCount":"1","resultStr":"{\"title\":\"Point object recognition — Some single- and multi-channel applications\",\"authors\":\"Peter Linde, Ralph Snel, Stefan Spännare\",\"doi\":\"10.1016/S0083-6656(97)00047-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>High-precision photometric analysis of images of crowded stellar fields needs sophisticated algorithms. The photometric precision is, however, a strong function of the completeness of source detection. We discuss several aspects of this problem, both with relation to single- and multi-channel applications. In single images, we separate detection into two phases, source image enhancement and actual detection. Comparative tests show a point spread function pixel fitting technique to give the best results. For the fraction of undetectable stars still affecting image statistics, we have developed a technique to extract information about their effect on the faint-end luminosity function. We give two examples of multi-channel image fusion applications: (1) a combination of low- and high-resolution images and (2) removal of undersampling effects by sub-pixel image displacements. Preliminary results show considerable potential for these techniques.</p></div>\",\"PeriodicalId\":101275,\"journal\":{\"name\":\"Vistas in Astronomy\",\"volume\":\"41 3\",\"pages\":\"Pages 419-426\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0083-6656(97)00047-0\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Vistas in Astronomy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0083665697000470\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vistas in Astronomy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0083665697000470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Point object recognition — Some single- and multi-channel applications
High-precision photometric analysis of images of crowded stellar fields needs sophisticated algorithms. The photometric precision is, however, a strong function of the completeness of source detection. We discuss several aspects of this problem, both with relation to single- and multi-channel applications. In single images, we separate detection into two phases, source image enhancement and actual detection. Comparative tests show a point spread function pixel fitting technique to give the best results. For the fraction of undetectable stars still affecting image statistics, we have developed a technique to extract information about their effect on the faint-end luminosity function. We give two examples of multi-channel image fusion applications: (1) a combination of low- and high-resolution images and (2) removal of undersampling effects by sub-pixel image displacements. Preliminary results show considerable potential for these techniques.