{"title":"EXPRESS:基于形态增强的滚动球基线去除算法。","authors":"Xiaoyang Li, Hanjun Zhang, Zhong Wang, Yuee Li","doi":"10.1177/00037028251384654","DOIUrl":null,"url":null,"abstract":"<p><p>As a preprocessing step of spectroscopic techniques such as Raman spectroscopy, infrared spectroscopy, electrophoresis, etc., the baseline correction is very important for improving the signal quality, thereby ensuring the reliability and accuracy of the data analysis. Methods such as polynomial fitting, wavelet transforms, and frequency-domain filtering are widely used for baseline correction, effectively reducing interference and enhancing the reliability of signal analysis. However, these methods have certain limitations: (i) Polynomial fitting faces challenges in determining the optimal order, which may affect the fitting quality, (ii) wavelet transforms are complex and require fine adjustments, and (iii) frequency-domain filtering may cause signal distortion. These shortcomings affect the implementation of the algorithm in spectral related industries. Therefore, finding an appropriate algorithm to optimize baseline removal is crucial for the development of automated spectral analysis equipment. Here, we propose a rolling ball baseline removal algorithm based on morphological operations. With its simple implementation and excellent baseline removal performance, this method effectively avoids the overfitting problems. It is suitable for baseline correction in not only Raman spectroscopy, but also various other types of spectral data. In all, this approach offers a convenient and efficient general solution for the processing of various spectral data.</p>","PeriodicalId":8253,"journal":{"name":"Applied Spectroscopy","volume":" ","pages":"37028251384654"},"PeriodicalIF":2.2000,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Morphology-Enhanced Rolling Ball Algorithm for Baseline Removal.\",\"authors\":\"Xiaoyang Li, Hanjun Zhang, Zhong Wang, Yuee Li\",\"doi\":\"10.1177/00037028251384654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>As a preprocessing step of spectroscopic techniques such as Raman spectroscopy, infrared spectroscopy, electrophoresis, etc., the baseline correction is very important for improving the signal quality, thereby ensuring the reliability and accuracy of the data analysis. Methods such as polynomial fitting, wavelet transforms, and frequency-domain filtering are widely used for baseline correction, effectively reducing interference and enhancing the reliability of signal analysis. However, these methods have certain limitations: (i) Polynomial fitting faces challenges in determining the optimal order, which may affect the fitting quality, (ii) wavelet transforms are complex and require fine adjustments, and (iii) frequency-domain filtering may cause signal distortion. These shortcomings affect the implementation of the algorithm in spectral related industries. Therefore, finding an appropriate algorithm to optimize baseline removal is crucial for the development of automated spectral analysis equipment. Here, we propose a rolling ball baseline removal algorithm based on morphological operations. With its simple implementation and excellent baseline removal performance, this method effectively avoids the overfitting problems. It is suitable for baseline correction in not only Raman spectroscopy, but also various other types of spectral data. In all, this approach offers a convenient and efficient general solution for the processing of various spectral data.</p>\",\"PeriodicalId\":8253,\"journal\":{\"name\":\"Applied Spectroscopy\",\"volume\":\" \",\"pages\":\"37028251384654\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Spectroscopy\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1177/00037028251384654\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INSTRUMENTS & INSTRUMENTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Spectroscopy","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1177/00037028251384654","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
Morphology-Enhanced Rolling Ball Algorithm for Baseline Removal.
As a preprocessing step of spectroscopic techniques such as Raman spectroscopy, infrared spectroscopy, electrophoresis, etc., the baseline correction is very important for improving the signal quality, thereby ensuring the reliability and accuracy of the data analysis. Methods such as polynomial fitting, wavelet transforms, and frequency-domain filtering are widely used for baseline correction, effectively reducing interference and enhancing the reliability of signal analysis. However, these methods have certain limitations: (i) Polynomial fitting faces challenges in determining the optimal order, which may affect the fitting quality, (ii) wavelet transforms are complex and require fine adjustments, and (iii) frequency-domain filtering may cause signal distortion. These shortcomings affect the implementation of the algorithm in spectral related industries. Therefore, finding an appropriate algorithm to optimize baseline removal is crucial for the development of automated spectral analysis equipment. Here, we propose a rolling ball baseline removal algorithm based on morphological operations. With its simple implementation and excellent baseline removal performance, this method effectively avoids the overfitting problems. It is suitable for baseline correction in not only Raman spectroscopy, but also various other types of spectral data. In all, this approach offers a convenient and efficient general solution for the processing of various spectral data.
期刊介绍:
Applied Spectroscopy is one of the world''s leading spectroscopy journals, publishing high-quality peer-reviewed articles, both fundamental and applied, covering all aspects of spectroscopy. Established in 1951, the journal is owned by the Society for Applied Spectroscopy and is published monthly. The journal is dedicated to fulfilling the mission of the Society to “…advance and disseminate knowledge and information concerning the art and science of spectroscopy and other allied sciences.”