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Revisiting the preprocessing procedures for elemental concentration estimation based on chemcam libs on mars rover

机译:根据Mars Rover的ChemCam Libs,重新审视元素浓度估计的预处理程序

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The ChemCam instrument package on the Mars rover, “Curiosity”, is the first planetary instrument that employs laser-induced breakdown spectroscopy (LIBS) to determine the compositions of geological samples on another planet. However, the sampled spectra are often corrupted by various sources of interferences that would largely affect the accuracy of elemental concentration estimation. Therefore, preprocessing is essential to improve the quality of the spectra. This paper revisits the conventional preprocessing procedures where denoising is followed by continuum removal. Through comprehensive performance evaluation, we propose a new procedure that would lead to much improved estimation accuracy. First, we show that the denoising process should be conducted after continuum removal. Second, a state-of-the-art image denoising technique is adapted to the 1D domain to boost the performance of denoising. Third, an additional preprocessing step is added that effectively select the most informative spectral bands. All these approaches have largely improved the accuracy of concentration estimation with band selection being the most effective.
机译:Mars Rover的ChemCam仪器包装是第一个采用激光诱导的击穿光谱(Libs)的行星仪器,以确定另一个星球上的地质样品的组成。然而,采样光谱通常由各种干扰源损坏,这主要影响元素浓度估计的准确性。因此,预处理对于提高光谱的质量至关重要。本文重新审视了常规预处理程序,其中去噪之后是连续的去除。通过全面的绩效评估,我们提出了一种将导致大量提高的估计准确性的新程序。首先,我们表明应在连续拆除后进行去噪过程。其次,最先进的图像去噪技术适用于1D域以提高去噪的性能。第三,添加了另外的预处理步骤,其有效地选择最具信息丰富的光谱频带。所有这些方法在很大程度上提高了带有频带选择的浓度估计的准确性是最有效的。

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