Conference Papers - 2014 by CHIMAN KWAN
The ChemCam instrument package on the Mars rover, " Curiosity " , is the first planetary instrume... more 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, pre-processing 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.
JMARS (Java Mission-planning
and Analysis for Remote Sensing) is a geospatial information
system ... more JMARS (Java Mission-planning
and Analysis for Remote Sensing) is a geospatial information
system (GIS) developed by ASU's Mars
Space Flight Facility to provide mission planning and
data analysis tools for NASA planetary mission data to
scientists, students of all ages, and to the general public
[1]. We developed a custom layer for JMARS to show
the traverse map of Mars rovers including Spirit, Opportunity
and Curiosity (see Fig. 1). The tool allows
users to easily view spectral measurements obtained by
the rovers (Fig. 2) and concentration results (Fig. 4)
generated by scientists. When a particular sol (Mars
day) is selected, the graphics window of the JMARS
software shows the location of the rover at that day
(see Fig. 3). In Fig. 1 and Fig. 3, we also load HiRISE
data layer to show the high resolution image of Mars.
Compositional analysis is important to interrogate spectral samples for direct analysis of materi... more Compositional analysis is important to interrogate spectral samples for direct analysis of materials in agriculture, environment and archaeology, etc. In this paper, multi-variate analysis (MVA) techniques are coupled with laser induced breakdown spectroscopy (LIBS) to estimate quantitative elemental compositions and determine the type of the sample. In particular, we present a new multivariate analysis method for composition analysis, referred to as "spectral unmixing". The LIBS spectrum of a testing sample is considered as a linear mixture with more than one constituent signatures that correspond to various chemical elements. The signature library is derived from regression analysis using training samples or is manually set up with the information from an elemental LIBS spectral database. A calibration step is used to make all the signatures in library to be homogeneous with the testing sample so as to avoid inhomogeneous signatures that might be caused by different sampling conditions. To demonstrate the feasibility of the proposed method, we compare it with the traditional partial least squares (PLS) method and the univariate method using a standard soil data set with elemental concentration measured a priori. The experimental results show that the proposed method holds great potential for reliable and effective elemental concentration estimation.
The ChemCam instrument package on the Mars rover, “Curiosity”, is the first planetary instrument ... more 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 info...
We developed a custom layer for JMARS to show the traverse map of Mars rovers including Spirit, O... more We developed a custom layer for JMARS to show the traverse map of Mars rovers including Spirit, Opportunity, and Curiosity.
IOP Conference Series: Earth and Environmental Science, 2014
Compositional analysis is important to interrogate spectral samples for direct analysis of materi... more Compositional analysis is important to interrogate spectral samples for direct analysis of materials in agriculture, environment and archaeology, etc. In this paper, multivariate analysis (MVA) techniques are coupled with laser induced breakdown spectroscopy (LIBS) to estimate quantitative elemental compositions and determine the type of the sample. In particular, we present a new multivariate analysis method for composition analysis, referred to as "spectral unmixing". The LIBS spectrum of a testing sample is considered as a linear mixture with more than one constituent signatures that correspond to various chemical elements. The signature library is derived from regression analysis using training samples or is manually set up with the information from an elemental LIBS spectral database. A calibration step is used to make all the signatures in library to be homogeneous with the testing sample so as to avoid inhomogeneous signatures that might be caused by different sampling conditions. To demonstrate the feasibility of the proposed method, we compare it with the traditional partial least squares (PLS) method and the univariate method using a standard soil data set with elemental concentration measured a priori. The experimental results show that the proposed method holds great potential for reliable and effective elemental concentration estimation.
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Conference Papers - 2014 by CHIMAN KWAN
and Analysis for Remote Sensing) is a geospatial information
system (GIS) developed by ASU's Mars
Space Flight Facility to provide mission planning and
data analysis tools for NASA planetary mission data to
scientists, students of all ages, and to the general public
[1]. We developed a custom layer for JMARS to show
the traverse map of Mars rovers including Spirit, Opportunity
and Curiosity (see Fig. 1). The tool allows
users to easily view spectral measurements obtained by
the rovers (Fig. 2) and concentration results (Fig. 4)
generated by scientists. When a particular sol (Mars
day) is selected, the graphics window of the JMARS
software shows the location of the rover at that day
(see Fig. 3). In Fig. 1 and Fig. 3, we also load HiRISE
data layer to show the high resolution image of Mars.