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http://hdl.handle.net/2080/1180
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| DC Field | Value | Language |
|---|
| contributor.author | Mishra, S K | - |
| contributor.author | Panda, G | - |
| contributor.author | Meher, S | - |
| date.accessioned | 2010-02-22T06:14:59Z | - |
| date.available | 2010-02-22T06:14:59Z | - |
| date.issued | 2009 | - |
| identifier.citation | International Journal of Recent Trends in Engineering, Vol. 1,No.1, May 2009 | en |
| identifier.uri | http://hdl.handle.net/2080/1180 | - |
| description.abstract | Here we have presented an alternate ANN
structure called functional link ANN (FLANN) for image
denoising. In contrast to a feed forward ANN structure i.e.
a multilayer perceptron (MLP), the FLANN is basically a
single layer structure in which non-linearity is introduced
by enhancing the input pattern with nonlinear function
expansion. In this work three different expansions is
applied. With the proper choice of functional expansion in
a FLANN , this network performs as good as and in some
case even better than the MLP structure for the problem
of denoising of an image corrupted with Salt and Pepper
noise. In the single layer functional link ANN (FLANN)
the need of hidden layer is eliminated. The novelty of this
structure is that it requires much less computation than
that of MLP. In the presence of additive white Gaussian
noise in the image, the performance of the proposed
network is found superior to that of a MLP .In particular
FLANN structure with Chebyshev functional expansion
works best for Salt and Pepper noise suppression from an
image. | en |
| format.extent | 515733 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | - |
| subject | MLP | en |
| subject | FLANN | en |
| subject | Chebyshev FLANN | en |
| subject | Salt and Pepper noise | en |
| title | Chebyshev Functional Link Artificial Neural Networks for Denoising of Image Corrupted by Salt and Pepper Noise | en |
| type | Article | en |
| Appears in Collections: | Journal Articles
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Description |
Size | Format |
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| sudhanshu1.pdf | | 503Kb | Adobe PDF | View/Open |
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