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A statistical theory for optimal detection of moving objects in variable corruptive noise

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4 Author(s)
Cheung, J.F.Y. ; U.S. Air Force Res. Lab., Rome, NY, USA ; Wicks, M.C. ; Genello, G.R.J. ; Kurz, L.

In this paper, the classical analysis of variance is extended to three-dimensional (3-D) Graeco-Latin squares design for multiframe processing applications. Conspicuous physical features, including edges, lines, and corners, can then be expressed as contrast functions. This enables the development of a new methodology for detecting moving objects embedded in noise. The new detector exploits spatial and temporal information uniformly most powerful in a Gaussian environment with unknown and time-varying noise variance. Also found is that a moving object detector based on contrast functions coincides with a sufficient statistic of the generalized likelihood ratio test. Extensive image analysis demonstrates the practicality of the detector and compares favorably to other classes of detectors

Published in:

Image Processing, IEEE Transactions on  (Volume:8 ,  Issue: 12 )

Date of Publication:

Dec 1999

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