Abstract:
In this paper, a hybrid classifier is introduced which combines
a linear discriminant classifier and a nonlinear nonparametric
neural network based classifier such as the Radial
Basis Function Neural Networks. This hybrid model
provides a linear parametric coding of the coarse-level information
about the underlying image, and then use the
neural networks to encode the finer-level information of
the same image. This model allows the selected image
regions of interest be analyzed and encoded in the finer
scales by a non-parametric neural network models whilst
the image regions of no-interest are analyzed and encoded
in coarse scales by a simple parametric model. The experiment
on video image compression shows that the proposed
model achieves significantly reduced computations for similar
compression performance compared to other conventional
methods.
