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Proceedings Paper

Discriminating a specified digital image from noise process
Author(s): Nicholas A. Nechval; Konstantin N. Nechval
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Paper Abstract

In this paper, the problem of discriminating a specified signal from noise process is considered, where the signal is associated with a digital image. In the univariate case it is well known that the one-sided t-test is uniformly most powerful for the null hypothesis against all one-sided alternatives. Such a property does not easily extend to the multivariate case. In the present paper, a test is derived for the hypothesis that the main of a vector random variable is zero against specified alternatives, when the covariance matrix is unknown. This test depends on the given alternatives and is more powerful than Hotelling's T. The test is invariant to intensity changes in a background of Gaussian noise and achieves a fixed probability of a false alarm. Thus, operating in accordance to the local noise situation, the test is adaptive. The properties of the proposed test are investigated when a single alternative is specified.

Paper Details

Date Published: 1 October 1998
PDF: 9 pages
Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); doi: 10.1117/12.323237
Show Author Affiliations
Nicholas A. Nechval, Aviation Univ. of Riga (Latvia)
Konstantin N. Nechval, Aviation Univ. of Riga (Latvia)

Published in SPIE Proceedings Vol. 3460:
Applications of Digital Image Processing XXI
Andrew G. Tescher, Editor(s)

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