{"title":"不同天气条件下自然背景和人造目标的日、长波高光谱测量分析","authors":"Christoph Borel-Donohue, D. Rosario, J. Romano","doi":"10.1109/AIPR.2014.7041903","DOIUrl":null,"url":null,"abstract":"In this paper we describe the end-to-end processing of image Fourier Transform spectrometry data taken at Picatinny Arsenal in New Jersey with the long-wave hyperspectral camera from Telops. The first part of the paper discusses the processing from raw data to calibrated radiance and emissivity data. Data was taken during several months under different weather conditions every 6 minutes from a 213ft high tower of surrogate tank targets for a project sponsored by the Army Research Laboratory in Adelphi, MD. An automatic calibration and analysis program was developed which creates calibrated data files and HTML files. The first processing stage is a flat-fielding. During this step the mean base line is used to find dead pixels (baseline low or at the maximum). Noisy pixels are detected where the standard deviation over the part of the interferogram. A flat-fielded and bad pixel corrected calibration cube using the gain and offset determined by a single blackbody measurement is created. In the second stage each flat-fielded cube is Fourier transformed and a 2-point radiometric calibration is performed. For selected cubes a temperature-emissivity separation algorithm is applied. The second part discusses environmental effects such as diurnal and seasonal atmospheric and temperature changes and the effect of cloud cover on the data. To test the effect of environmental conditions the range-invariant anomaly detection approach is applied to calibrated radiance, brightness temperature and emissivity data.","PeriodicalId":210982,"journal":{"name":"2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of diurnal, long-wave hyperspectral measurements of natural background and manmade targets under different weather conditions\",\"authors\":\"Christoph Borel-Donohue, D. Rosario, J. Romano\",\"doi\":\"10.1109/AIPR.2014.7041903\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we describe the end-to-end processing of image Fourier Transform spectrometry data taken at Picatinny Arsenal in New Jersey with the long-wave hyperspectral camera from Telops. The first part of the paper discusses the processing from raw data to calibrated radiance and emissivity data. Data was taken during several months under different weather conditions every 6 minutes from a 213ft high tower of surrogate tank targets for a project sponsored by the Army Research Laboratory in Adelphi, MD. An automatic calibration and analysis program was developed which creates calibrated data files and HTML files. The first processing stage is a flat-fielding. During this step the mean base line is used to find dead pixels (baseline low or at the maximum). Noisy pixels are detected where the standard deviation over the part of the interferogram. A flat-fielded and bad pixel corrected calibration cube using the gain and offset determined by a single blackbody measurement is created. In the second stage each flat-fielded cube is Fourier transformed and a 2-point radiometric calibration is performed. For selected cubes a temperature-emissivity separation algorithm is applied. The second part discusses environmental effects such as diurnal and seasonal atmospheric and temperature changes and the effect of cloud cover on the data. To test the effect of environmental conditions the range-invariant anomaly detection approach is applied to calibrated radiance, brightness temperature and emissivity data.\",\"PeriodicalId\":210982,\"journal\":{\"name\":\"2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2014.7041903\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2014.7041903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of diurnal, long-wave hyperspectral measurements of natural background and manmade targets under different weather conditions
In this paper we describe the end-to-end processing of image Fourier Transform spectrometry data taken at Picatinny Arsenal in New Jersey with the long-wave hyperspectral camera from Telops. The first part of the paper discusses the processing from raw data to calibrated radiance and emissivity data. Data was taken during several months under different weather conditions every 6 minutes from a 213ft high tower of surrogate tank targets for a project sponsored by the Army Research Laboratory in Adelphi, MD. An automatic calibration and analysis program was developed which creates calibrated data files and HTML files. The first processing stage is a flat-fielding. During this step the mean base line is used to find dead pixels (baseline low or at the maximum). Noisy pixels are detected where the standard deviation over the part of the interferogram. A flat-fielded and bad pixel corrected calibration cube using the gain and offset determined by a single blackbody measurement is created. In the second stage each flat-fielded cube is Fourier transformed and a 2-point radiometric calibration is performed. For selected cubes a temperature-emissivity separation algorithm is applied. The second part discusses environmental effects such as diurnal and seasonal atmospheric and temperature changes and the effect of cloud cover on the data. To test the effect of environmental conditions the range-invariant anomaly detection approach is applied to calibrated radiance, brightness temperature and emissivity data.