Mathematics – Logic
Scientific paper
Dec 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufm.p51e1164p&link_type=abstract
American Geophysical Union, Fall Meeting 2009, abstract #P51E-1164
Mathematics
Logic
[5410] Planetary Sciences: Solid Surface Planets / Composition, [5464] Planetary Sciences: Solid Surface Planets / Remote Sensing, [5494] Planetary Sciences: Solid Surface Planets / Instruments And Techniques, [6221] Planetary Sciences: Solar System Objects / Europa
Scientific paper
Jupiter's moon Europa likely possesses an ocean of liquid water beneath its icy surface, but estimates of the thickness of the surface ice shell vary from a few kilometers to tens of kilometers. Color images of Europa reveal the existence of a reddish, non-ice component associated with a variety of geological features. The composition and origin of this material is uncertain, as is its relationship to Europa's various landforms. Published analyses of Galileo Near Infrared Mapping Spectrometer (NIMS) observations indicate the presence of highly hydrated sulfate compounds. This non-ice material may also bear biosignatures or other signs of biotic material. Additional spectral information from the Galileo Solid State Imager (SSI) could further elucidate the nature of the surface deposits, particularly when combined with information from the NIMS. However, little effort has been focused on this approach because proper calibration of the color image data is challenging, requiring both skill and patience to process the data and incorporate the appropriate scattered light correction. We are currently working to properly calibrate the color SSI data. The most important and most difficult issue to address in the analysis of multispectral SSI data entails using thorough calibrations and a correction for scattered light. Early in the Galileo mission, studies of the Galileo SSI data for the moon revealed discrepancies of up to 10% in relative reflectance between images containing scattered light and images corrected for scattered light. Scattered light adds a wavelength-dependent low-intensity brightness factor to pixels across an image. For example, a large bright geological feature located just outside the field of view of an image will scatter extra light onto neighboring pixels within the field of view. Scattered light can be seen as a dim halo surrounding an image that includes a bright limb, and can also come from light scattered inside the camera by dirt, edges, and the interfaces of lenses. Because of the wavelength dependence of this effect, a scattered light correction must be performed on any SSI multispectral dataset before quantitative spectral analysis can be done. The process involves using a point-spread function for each filter that helps determine the amount of scattered light expected for a given pixel based on its location and the model attenuation factor for that pixel. To remove scattered light for a particular image taken through a particular filter, the Fourier transform of the attenuation function, which is the point spread function for that filter, is convolved with the Fourier transform of the image at the same wavelength. The result is then filtered for noise in the frequency domain, and then transformed back to the spatial domain. This results in a version of the original image that would have been taken without the scattered light contribution. We will report on our initial results from this calibration.
Phillips Cynthia B.
Valenti M.
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