A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data
Hyperspectral remote sensing is crucial due to its continuous spectral information, especially in the quantitative remote sensing (QRS) field. Surface reflectance (SR), a fundamental product in QRS, can play a pivotal role in application accuracy and serves as a key indicator of sensor performance....
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MDPI AG
2025-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/11/1844 |
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| author | Qiongqiong Lan Yaqing He Qijin Han Yongguang Zhao Wan Li Lu Xu Dongping Ming |
| author_facet | Qiongqiong Lan Yaqing He Qijin Han Yongguang Zhao Wan Li Lu Xu Dongping Ming |
| author_sort | Qiongqiong Lan |
| collection | DOAJ |
| description | Hyperspectral remote sensing is crucial due to its continuous spectral information, especially in the quantitative remote sensing (QRS) field. Surface reflectance (SR), a fundamental product in QRS, can play a pivotal role in application accuracy and serves as a key indicator of sensor performance. However, the distinctive spectral characteristics of a hyperspectral image (HSI) make it particularly susceptible to noise during the process of imaging, which inevitably degrades data quality and reduces SR accuracy. Moreover, the validation of hyperspectral SR faces challenges due to the scarcity of reliable validation data. To address these issues, aiming at fast and efficient processing of Chinese domestic ZY1-02D hyperspectral level-1 data, this study proposes a comprehensive processing framework: (1) To address the low efficiency of traditional bad line detection by visual examination, an automatic bad line detection method based on the pixel grayscale gradient threshold algorithm is proposed; (2) A spectral correlation-based interpolation method is developed to overcome the poor performance of adjacent-column averaging in repairing wide bad lines; (3) A reliable validation method was established based on the spectral band adjustment factors method to compare hyperspectral SR with multispectral SR and in-situ ground measurements. The results and analysis demonstrate that the proposed method improves the accuracy of ZY1-02D SR and the method ensures high processing efficiency, requiring only 5 min per scene of ZY1-02D HSI. This study provides a technical foundation for the application of ZY1-02D HSIs and offers valuable insights for the development and enhancement of next-generation hyperspectral sensors. |
| format | Article |
| id | doaj-art-3e087ff86a2d4f5fbb3754b41f6d89cd |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-3e087ff86a2d4f5fbb3754b41f6d89cd2025-08-20T03:46:42ZengMDPI AGRemote Sensing2072-42922025-05-011711184410.3390/rs17111844A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral DataQiongqiong Lan0Yaqing He1Qijin Han2Yongguang Zhao3Wan Li4Lu Xu5Dongping Ming6China Centre for Resources Satellite Data and Application, Beijing 100094, ChinaSchool of Information Engineering, China University of Geosciences (Beijing), Beijing 100083, ChinaChina Centre for Resources Satellite Data and Application, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaSchool of Information Engineering, China University of Geosciences (Beijing), Beijing 100083, ChinaSchool of Information Engineering, China University of Geosciences (Beijing), Beijing 100083, ChinaHyperspectral remote sensing is crucial due to its continuous spectral information, especially in the quantitative remote sensing (QRS) field. Surface reflectance (SR), a fundamental product in QRS, can play a pivotal role in application accuracy and serves as a key indicator of sensor performance. However, the distinctive spectral characteristics of a hyperspectral image (HSI) make it particularly susceptible to noise during the process of imaging, which inevitably degrades data quality and reduces SR accuracy. Moreover, the validation of hyperspectral SR faces challenges due to the scarcity of reliable validation data. To address these issues, aiming at fast and efficient processing of Chinese domestic ZY1-02D hyperspectral level-1 data, this study proposes a comprehensive processing framework: (1) To address the low efficiency of traditional bad line detection by visual examination, an automatic bad line detection method based on the pixel grayscale gradient threshold algorithm is proposed; (2) A spectral correlation-based interpolation method is developed to overcome the poor performance of adjacent-column averaging in repairing wide bad lines; (3) A reliable validation method was established based on the spectral band adjustment factors method to compare hyperspectral SR with multispectral SR and in-situ ground measurements. The results and analysis demonstrate that the proposed method improves the accuracy of ZY1-02D SR and the method ensures high processing efficiency, requiring only 5 min per scene of ZY1-02D HSI. This study provides a technical foundation for the application of ZY1-02D HSIs and offers valuable insights for the development and enhancement of next-generation hyperspectral sensors.https://www.mdpi.com/2072-4292/17/11/1844hyperspectral remote sensingsurface reflectancehyperspectral denoisingZY1-02D |
| spellingShingle | Qiongqiong Lan Yaqing He Qijin Han Yongguang Zhao Wan Li Lu Xu Dongping Ming A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data Remote Sensing hyperspectral remote sensing surface reflectance hyperspectral denoising ZY1-02D |
| title | A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data |
| title_full | A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data |
| title_fullStr | A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data |
| title_full_unstemmed | A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data |
| title_short | A Fast and Efficient Denoising and Surface Reflectance Retrieval Method for ZY1-02D Hyperspectral Data |
| title_sort | fast and efficient denoising and surface reflectance retrieval method for zy1 02d hyperspectral data |
| topic | hyperspectral remote sensing surface reflectance hyperspectral denoising ZY1-02D |
| url | https://www.mdpi.com/2072-4292/17/11/1844 |
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