In-flight calibration and performance of the Mars Exploration Rover Panoramic Camera (Pancam) instruments

The Mars Exploration Rover Panoramic Camera ( MER/Pancam) instruments have acquired more than 60,000 high-resolution, multispectral, stereoscopic images of soil, rocks, and sky at the Gusev crater and Meridiani Planum landing sites since January 2004. These images, combined with other MER data sets, have enabled new discoveries about the composition, mineralogy, and geologic/geochemical evolution of both sites. One key to the success of Pancam in contributing to the overall success of MER has been the development of a calibration pipeline that can quickly remove instrumental artifacts and generate both absolute radiance and relative reflectance images with high accuracy and precision in order to influence tactical rover driving and in situ sampling decisions. This paper describes in detail the methods, assumptions, and models/algorithms in the calibration pipeline developed for Pancam images, based on new measurements and refinements performed primarily from flight data acquired on Mars. Major calibration steps include modeling and removal of detector bias signal, active and readout region dark current, electronic "shutter smear,'' and pixel-to-pixel responsivity ( flatfield) variations. Pancam images are calibrated to radiance ( W/m(2)/nm/sr) using refined preflight-derived calibration coefficients, or radiance factor ( I/F) using near-in-time measurements of the Pancam calibration target and a model of aeolian dust deposition on the target as a function of time. We are able to verify that the absolute radiance calibration of most Pancam images is accurate to within about 10% or less and that the filter-to-filter and pixel-to-pixel precision of the calibrated relative reflectance data ( both based on measurements of the Pancam calibration target) are typically about 3% and 1% or less, respectively. Examples are also presented of scientific applications made possible by the high fidelity of the calibrated Pancam data. These include 11-color visible to near-IR spectral analysis, calculation of "true color'' and chromaticity values, and generation of "super resolution'' image data products. This work represents a follow-on and enhancement to the Pancam preflight calibration process described by Bell et al. ( 2003).