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Spectral feature design in high dimensional multispectral dataThe High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.
Document ID
19900015348
Acquisition Source
Legacy CDMS
Document Type
Contractor Report (CR)
Authors
Chen, Chih-Chien Thomas (Purdue Univ. West Lafayette, IN, United States)
Landgrebe, David A. (Purdue Univ. West Lafayette, IN, United States)
Date Acquired
September 6, 2013
Publication Date
August 1, 1988
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
NASA-CR-186647
NAS 1.26:186647
TR-EE-88-35
Accession Number
90N24664
Funding Number(s)
CONTRACT_GRANT: NAGW-925
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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