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Image and Video ProcessingWith
the enormous growth
of visual information in digital form, the interest in image and video
processing applications is increasing dramatically. At the heart of
many image processing tasks, there is an efficient
image representation that can capture significant information of an
image in a compact form. Over the last decade or so, the wavelet
transform has emerged as the dominating tool in image processing. The
success of the wavelet transform is mainly due to its ability to
characterize certain classes of signals with few transform
coefficients. In particular, wavelets as time-frequency localized bases
are particularly suited to represent one dimensional (1-D) piecewise
smooth functions.
In two dimensions (2-D), the situation is much more open. Despite their widespread success in image processing, wavelets are not adequate at representing images. In images, discontinuities are straight line or smooth curves. The 2-D wavelet transform is a separable transform given by the tensor-product of two 1-D wavelets along the horizontal and vertical directions. For this reason, this separable transform is good at isolating horizontal and vertical edges, but it is not adequate at treating more complex discontinuities. This indicates that more powerful image representations are needed. We are investigating the use of quadtree decompositions and of directional wavelets to overcome the limitations of the separable wavelet transform. Main Publications:
Collaborations and Interactions: M. Vetterli (EPFL), M. Do (UIUC). |
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