The Effect of the Image Local Mean on the Two-dimensional Least Mean Square Algorithm Weight Convergence |
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| Authors: | Mohiy M Hadhoud David W Thomas |
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| Affiliation: | 1. Faculty of Electronic Engineering , Menoufia University , Menouf, Egypt;2. Department of Electronics and Computer Science , The University , Southampton, England |
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| Abstract: | Abstract This paper discusses the effect of an image's non-zero local mean value on the mean square estimation error (MSEE) and the steady-state weights of the two-dimensional least mean square (TDLMS) algorithm 1] when used in image processing. It shows that the local mean causes an increase in the MSEE which is proportional to the square of the image's local mean value. This causes the filter to converge to non-optimum weights and the shift from the optimum values is proportional to the square of the image's local mean value. It is shown that this effect can be reduced by normalizing the filter's weights to unity. |
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