IMRAN: a noise estimation method for relative radiometric calibration data
文献类型：期刊论文
| 作者 | Yu, Kai1; Zhao, Yongchao1; Liu, Suhong1 |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2015 |
| 卷号 | 36期号:16页码:4037-4053 |
| 通讯作者 | Liu, SH (reprint author), Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China. |
| 英文摘要 | Radiometric calibration is the foundation for remote sensors to accurately record the reflected energy from targets and to also effectively display the reflectance diversity among them. As one of the calibration methods, pre-launch laboratory relative calibration is essentially a normalizing process for each detector of a sensor at different intensity levels of various radiation sources. However, interferences such as stray light, dark current, and stochastic noise will cause some deviation of the normalizing correction factor. In this article, we propose an integral noise (a combination of the aforementioned three noises) estimation method based on the correlation between the elements of the calibration data itself. Abbreviated as IMRAN (Iterative Maximal Residual As Noise), this method is an iteration procedure using least square fitting to calculate the maximum residual of the sensor pixel in question against the rest sensor pixels and to consider this value as the estimated noise. The iteration is continued after subtracting the noise from the raw data of the sensor pixel until the noise estimation gets converged and then the accumulation of the results from each round is the final estimated noise. And this procedure is applied to every sensor pixel. The verification results demonstrated the IMRAN method can effectively estimate the integral noise of pre-launch radiometric calibration data and substantially improve its precision. When the number of radiation level increases, the precision of the estimated noise will be rapidly increased, whereas the number of sensor pixels has no obvious effect. Because this IMRAN method uses the data of every sensor pixel, it is sensitive to the outlier, which can be eliminated by variance detection as part of the IMRAN method. |
| 研究领域[WOS] | Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000359970900007 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38506]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Yu, Kai 2.Liu, Suhong] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China 3.[Yu, Kai 4.Liu, Suhong] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China 5.[Yu, Kai 6.Liu, Suhong] Chinese Acad Sci, Inst Remote Sensing Applicat, Beijing 100875, Peoples R China 7.[Yu, Kai 8.Zhao, Yongchao] Chinese Acad Sci, Inst Elect, Key Lab Technol Geospatial Informat Proc & Applic, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Kai,Zhao, Yongchao,Liu, Suhong. IMRAN: a noise estimation method for relative radiometric calibration data[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2015,36(16):4037-4053. |
| APA | Yu, Kai,Zhao, Yongchao,&Liu, Suhong.(2015).IMRAN: a noise estimation method for relative radiometric calibration data.INTERNATIONAL JOURNAL OF REMOTE SENSING,36(16),4037-4053. |
| MLA | Yu, Kai,et al."IMRAN: a noise estimation method for relative radiometric calibration data".INTERNATIONAL JOURNAL OF REMOTE SENSING 36.16(2015):4037-4053. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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