the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
In-Flight Estimation of Instrument Spectral Response Functions Using Sparse Representations
Abstract. Accurate estimates of Instrument Spectral Response Functions (ISRFs) are crucial in order to have a good characterization of high resolution spectrometers. Spectrometers are composed of different optical elements that can induce errors in the measurements and therefore need to be modeled as accurately as possible. Parametric models are currently used to estimate these response functions. However, these models cannot always take into account the diversity of ISRF shapes that are encountered in practical applications. This paper studies a new ISRF estimation method based on a sparse representation of atoms belonging to a dictionary. This method is applied to different high-resolution spectrometers in order to assess its reproducibility for multiple remote sensing missions. The proposed method is shown to be very competitive when compared to the more commonly used parametric models, and yields normalized ISRF estimation errors less than 1 %.
Status: open (until 04 Aug 2024)
-
CC1: 'Comment on egusphere-2024-1120', Laurent Ferro-Famil, 08 Jun 2024
reply
The use of an iterative and dictionary-based based approach for estimating ISRFs is a rather original solution. The fact that the most simple method, SVD + OMP, eventually leads to the best performance is a very good, yet somehow surprising, news, and could be further commented: has this to do with a particular choice of the hyper-parameter in (8) or with a lack of discrimination of the L1 norm constraint? The iterations between dictionary estimates and sparse approximation represent an important aspect of the study, and could be further described. The adaptation to calibration errors, and temporal drifts of the feature represent high potential perspectives for this work.
Citation: https://doi.org/10.5194/egusphere-2024-1120-CC1
Viewed
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
126 | 0 | 0 | 126 | 0 | 0 |
- HTML: 126
- PDF: 0
- XML: 0
- Total: 126
- BibTeX: 0
- EndNote: 0
Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1