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Results for “multispectral”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Signature extension techniques applied to multispectral scanner data.

Review of a number of spectral radiance signature extension techniques based on the concept of preprocessing the data to reduce the effects due to atmospheric effects, scanner look angle, etc. One of the promising methods studied to date involves using a ratio preprocessing transformation wherein the signals generated in adjacent spectral bands are ratioed on a point-by-point basis prior to classification. This method is easily and efficiently implemented and tests to date have yielded excellent results. Signatures have been successfully extended over 100+ miles, four days, different times of day, and very different atmospheric conditions.

Nalepka, R. F.↗
NASA NTRS1974

Multispectral signatures in relation to ground control signature using nested sampling approach

The author has identified the following significant results. Principal effort has been on the development of a PDP-10 software package to read the CCT tapes more cheaply and rapidly. This is 90% completed and debugged. A shade print example of Treasure Island is provided. Stanford area was overflown with the U-2 as an add-on photographic mission to help fill in record-gaps in ERTS-1 overpass which was clouded out.

Lyon, R. J. P.↗
NASA NTRS1973

Choice: 36 band feature selection software with applications to multispectral pattern recognition

Feature selection software was developed at the Earth Resources Laboratory that is capable of inputting up to 36 channels and selecting channel subsets according to several criteria based on divergence. One of the criterion used is compatible with the table look-up classifier requirements. The software indicates which channel subset best separates (based on average divergence) each class from all other classes. The software employs an exhaustive search technique, and computer time is not prohibitive. A typical task to select the best 4 of 22 channels for 12 classes takes 9 minutes on a Univac 1108 computer.

Jones, W. C.↗