An adaptive linear system framework for image distortion analysis
To appear in:
Proc. 12th IEEE Int'l Conf on Image Processing
Genoa, Italy. September 2005.
© IEEE Computer Society.
We describe a framework for decomposing the distortion between two
images into a linear combination of components. Unlike conventional
linear bases such as those in Fourier or wavelet decompositions, a
subset of the components in our representation are not fixed, but are
adaptively computed from the input images. We show that this
framework is a generalization of a number of existing image comparison
approaches. As an example of a specific implementation, we select the
components based on the structural similarity principle, separating
the overall image distortions into non-structural distortions (those
that do not change the structures of the objects in the scene) and the
remaining structural distortions. We demonstrate that the resulting
measure is effective in predicting image distortions as perceived by
human observers.
Download:
Full Text (284kb, pdf)
/ Other Online Publications