Retinex Image Processing--Publications--SPIE 6246, Orlando, Florida
Automated, on-board terrain analysis for precision landings
Zia-ur Rahman, Daniel J. Jobson, Glenn A. Woodell, Glenn D. Hines
Advances in space robotics technology hinge to a large extent upon the
development and deployment of sophisticated new vision-based methods for
automated in-space mission operations and scientific survey. To this
end, we have developed a new concept for automated terrain analysis that
is based upon a generic image enhancement platform---multi-scale retinex
(MSR) and visual servo (VS) processing. This
pre-conditioning with the MSR and the VS produces a
``canonical'' visual representation that is largely independent of
lighting variations, and exposure errors. Enhanced imagery is then
processed with a biologically inspired two-channel edge detection
process, followed by a smoothness based criteria for image segmentation.
Landing sites can be automatically determined by examining the results
of the smoothness-based segmentation which shows those areas in the
image that surpass a minimum degree of smoothness. Though the MSR
has proven to be a very strong enhancement engine, the other elements of
the approach---the VS, terrain map generation, and
smoothness-based segmentation---are in early stages of development.
Experimental results on data from the Mars Global Surveyor show that the
imagery can be processed to automatically obtain smooth landing sites.
In this paper, we describe the method used to obtain these landing
sites, and also examine the smoothness criteria in terms of the imager
and scene characteristics. Several examples of applying this method to
simulated and real imagery are shown.