An adaptive robust regression method: Application to galaxy spectrum baseline estimation

Raphael Bacher 1 Florent Chatelain 2 Olivier Michel 1
1 GIPSA-CICS - CICS
GIPSA-DIS - Département Images et Signal
2 GIPSA-SAIGA - SAIGA
GIPSA-DA - Département Automatique, GIPSA-DIS - Département Images et Signal
Abstract : In this paper, a new robust regression method based on the Least Trimmed Squares (LTS) is proposed. The novelty of this approach consists in a simple adaptive estimation of the number of outliers. This method can be applied to baseline estimation, for example to improve the detection of gas spectral signature in astronomical hy-perspectral data such as those produced by the new Multi Unit Spec-troscopic Explorer (MUSE) instrument. To do so a method following the general idea of the LOWESS algorithm, a classical robust smoothing method, is developed. It consists in a windowed local linear regression, the local regression being done here by the new adap-tive LTS approach. The developed method is compared with state-of-the art baseline estimated algorithms on simulated data closed to the real data produced by the MUSE instrument.
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Communication dans un congrès
41st IEEE International Conference on Acoustics, Speech and SIgnal Processing (ICASSP 2016), Mar 2016, Shanghai, China. ICASSP 2016 - Proceedings, pp.4423 - 4427, 2016, Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on. 〈10.1109/ICASSP.2016.7472513〉
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Raphael Bacher, Florent Chatelain, Olivier Michel. An adaptive robust regression method: Application to galaxy spectrum baseline estimation. 41st IEEE International Conference on Acoustics, Speech and SIgnal Processing (ICASSP 2016), Mar 2016, Shanghai, China. ICASSP 2016 - Proceedings, pp.4423 - 4427, 2016, Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on. 〈10.1109/ICASSP.2016.7472513〉. 〈hal-01462974〉

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