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End-to-End Simulation and Analytical Model of Remote-Sensing Systems: Application to CRISM
- Source :
- IEEE Transactions on Geoscience and Remote Sensing.
- Publication Year :
- 2010
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2010.
-
Abstract
- The simulation of remote-sensing hyperspectral images is a useful tool for a variety of tasks such as the design of systems, the understanding of the image formation process, and the development and validation of data processing algorithms. The lack of ground truth and the incomplete knowledge of the Martian environment make simulation studies of Mars hyperspectral images a useful tool for automated analysis of Mars data. Hyperspectral near-infrared scenes of mineral mixtures have been simulated to analyze the contributions of surface minerals, atmosphere, and sensor noise on images of Mars. Modeling the remote-sensing process creates a means for the independent analysis of the influence of the environment and instruments on the detection accuracy of the surface composition (e.g., the scene endmembers). The end-to-end model builds surface reflectance scenes based on laboratory sample spectra, creates atmospheric effects using radiative transfer routines, simulates the instrument response function using CRISM data files, and adds instrument noise from thermal and other sources. The purpose of this paper is to understand the hyperspectral remote-sensing process to eventually enable the elevated detection accuracy of minerals on the surface of Mars. The viability of a linear approximation of the complete model is also investigated. The approximation is compared to the complete model in an image classification task.
- Subjects :
- Image formation
Ground truth
Pixel
Contextual image classification
business.industry
Computer science
Hyperspectral imaging
Mars Exploration Program
Atmospheric model
Reflectivity
Spectral line
CRISM
Atmosphere
Radiative transfer
General Earth and Planetary Sciences
Computer vision
Artificial intelligence
Noise (video)
Electrical and Electronic Engineering
business
Remote sensing
Subjects
Details
- ISSN :
- 15580644 and 01962892
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Geoscience and Remote Sensing
- Accession number :
- edsair.doi...........fc39dbafa9b4894683bbefb7054827a8