We present an algorithm for the application of support vector machine (SVM) learning to
image compression. The algorithm combines SVMs with the discrete cosine transform
(DCT). Unlike a classic radial basis function networks or multilayer perceptrons that require
the topology of the network to be defined before training, an SVM selects the minimum
number of training points, called support vectors, that ensure modeling of the data within the
given level of accuracy (aka insensitivity zone/spl epsi/). It is this property that is exploited as …

Combining support vector machine learning with the discrete cosine transform in image
compression | UOBScholar Hub … Title: Combining support vector machine learning with
the discrete cosine transform in image compression Authors: Dayaa, Fadi … Advisors:
Dagher, Issam Subjects: Image compression Issue Date: 2007 Description: …