A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager
Thermal infrared hyperspectral imager is one of the frontier payloads in current hyperspectral remote sensing research. It has broad application prospects in land and ocean temperature inversion, environmental monitoring, and other fields. However, due to the influence of the production process of t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/19/7403 |
| _version_ | 1827652981980397568 |
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| author | Bingxin Liu Yulong Du Chengyu Liu Ying Li |
| author_facet | Bingxin Liu Yulong Du Chengyu Liu Ying Li |
| author_sort | Bingxin Liu |
| collection | DOAJ |
| description | Thermal infrared hyperspectral imager is one of the frontier payloads in current hyperspectral remote sensing research. It has broad application prospects in land and ocean temperature inversion, environmental monitoring, and other fields. However, due to the influence of the production process of the infrared focal plane array and the characteristics of the material itself, the infrared focal plane array inevitably has blind pixels, resulting in spectral distortion of the data or even invalid data, which limits the application of thermal infrared hyperspectral data. Most of the current blind pixels detection methods are based on the spatial dimension of the image, that is, processing single-band area images. The push-broom thermal infrared hyperspectral imager works completely different from the conventional area array thermal imager, and only one row of data is obtained per scan. Therefore, the current method cannot be directly applied to blind pixels detection of push-broom thermal infrared hyperspectral imagers. Based on the imaging principle of push-broom thermal infrared hyperspectral imager, we propose a practical blind pixels detection method. The method consists of two stages to detect and repair four common types of blind pixels: dead pixel, dark current pixel, blinking pixel, and noise pixel. In the first stage, dead pixels and dark current pixels with a low spectral response rate are detected by spectral filter detection; noise pixels are detected by spatial noise detection; and dark current pixels with a negative response slope are detected by response slope detection. In the second stage, according to the random appearance of blinking pixels, spectral filter detection is used to detect and repair spectral anomalies caused by blinking pixels line by line. In order to verify the effectiveness of the proposed method, a flight test was carried out, using the Airborne Thermal-infrared Hyperspectral Imaging System (ATHIS), the latest thermal infrared imager in China, for data acquisition. The results show that the method proposed in this paper can accurately detect and repair blind pixel, thus effectively eliminating spectral anomalies and significantly improving image quality. |
| first_indexed | 2024-03-09T21:10:41Z |
| format | Article |
| id | doaj.art-000d353c4da94f2e9af881616066b87b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:10:41Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-000d353c4da94f2e9af881616066b87b2023-11-23T21:48:39ZengMDPI AGSensors1424-82202022-09-012219740310.3390/s22197403A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral ImagerBingxin Liu0Yulong Du1Chengyu Liu2Ying Li3Navigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaKey Laboratory of Space Active Opto-Electronic Technologies, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaThermal infrared hyperspectral imager is one of the frontier payloads in current hyperspectral remote sensing research. It has broad application prospects in land and ocean temperature inversion, environmental monitoring, and other fields. However, due to the influence of the production process of the infrared focal plane array and the characteristics of the material itself, the infrared focal plane array inevitably has blind pixels, resulting in spectral distortion of the data or even invalid data, which limits the application of thermal infrared hyperspectral data. Most of the current blind pixels detection methods are based on the spatial dimension of the image, that is, processing single-band area images. The push-broom thermal infrared hyperspectral imager works completely different from the conventional area array thermal imager, and only one row of data is obtained per scan. Therefore, the current method cannot be directly applied to blind pixels detection of push-broom thermal infrared hyperspectral imagers. Based on the imaging principle of push-broom thermal infrared hyperspectral imager, we propose a practical blind pixels detection method. The method consists of two stages to detect and repair four common types of blind pixels: dead pixel, dark current pixel, blinking pixel, and noise pixel. In the first stage, dead pixels and dark current pixels with a low spectral response rate are detected by spectral filter detection; noise pixels are detected by spatial noise detection; and dark current pixels with a negative response slope are detected by response slope detection. In the second stage, according to the random appearance of blinking pixels, spectral filter detection is used to detect and repair spectral anomalies caused by blinking pixels line by line. In order to verify the effectiveness of the proposed method, a flight test was carried out, using the Airborne Thermal-infrared Hyperspectral Imaging System (ATHIS), the latest thermal infrared imager in China, for data acquisition. The results show that the method proposed in this paper can accurately detect and repair blind pixel, thus effectively eliminating spectral anomalies and significantly improving image quality.https://www.mdpi.com/1424-8220/22/19/7403thermal infraredhyperspectral imagerblind pixel |
| spellingShingle | Bingxin Liu Yulong Du Chengyu Liu Ying Li A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager Sensors thermal infrared hyperspectral imager blind pixel |
| title | A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager |
| title_full | A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager |
| title_fullStr | A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager |
| title_full_unstemmed | A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager |
| title_short | A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager |
| title_sort | practical method for blind pixel detection for the push broom thermal infrared hyperspectral imager |
| topic | thermal infrared hyperspectral imager blind pixel |
| url | https://www.mdpi.com/1424-8220/22/19/7403 |
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