Pulse-coupled neural network shadow compensation

John L. Johnson; Jaime R. Taylor; Matthew Anderson

doi:10.1117/12.342901

22 March 1999 Pulse-coupled neural network shadow compensation

John L. Johnson, Jaime R. Taylor, Matthew Anderson

Proceedings Volume 3722, Applications and Science of Computational Intelligence II; (1999) https://doi.org/10.1117/12.342901
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

The Pulsed Coupled Neural Network (PCNN) algorithm, when modified for use as an image processor, provides a unique method of multiplicative image decomposition (PCNN factorization). Because the factorization is ordered by levels of scene contrast, the first few factors contain the strong contrasts generally associated with shadows. The PCNN factorization effectively and automatically finds scene shadows. This is further developed here as a computationally effective shadow compensation algorithm with illustrative examples given, and is shown to be significantly more effective than histogram equalization. The advantage and disadvantages are discussed.

Citation Download Citation

John L. Johnson, Jaime R. Taylor, and Matthew Anderson "Pulse-coupled neural network shadow compensation", Proc. SPIE 3722, Applications and Science of Computational Intelligence II, (22 March 1999); https://doi.org/10.1117/12.342901

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