Maj Travis Blake (Air Force Institute of Technology), Lt Col Matthew E. Goda (Air Force Institute of Technology), Dr. Stephen C. Cain
(Air Force Institute of Technology), Kenneth J. Jerkatis (Boeing SVS)
Keywords: Imaging
Abstract:
Spectral images of terrestial objects as provided a wealth of information beyond the tradidtional data provided in a panchromatic image. What has proven to be successful for terrestial applications, can also be applied to images of objects in space.
This research expands on previous work discussing the image processing for data collected by the new AEOS Spectral Imaging Sensor (ASIS). ASIS uses broadband filters to collect AO compensated spectral images of astronomical objects and satellites. The use of the broadband filters spectrally blurs the images collected by ASIS. A post-processing algorithm called Model-Based Spectral Image Reconstruction (MBSIR) can simultaneously remove much of the spatial and spectral blurring in the sensor.
This paper will start by briefly reviewing the development of the MBSIR algorithm. The paper will then show the benefit of the post-processing algorithm on data collected in a laboratory set-up. A spectral source was imaged with the same filter, and therefore the same spectral blurring, as those used in ASIS. The results show that the spectral features in the source are not resolvable before applying the MBSIR algorithm and are resolvable after applying the algorithm to the data. Finally, the algorithm is applied to astronomical data collected with ASIS.
Date of Conference: September 10-14, 2006
Track: Imaging