Imperial College

Research Group

Image and Video Processing

With 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:

PhD Students:  Pancham Shukla, Rahul Shukla (at EPFL)   and  Vladan Velisavlievic (at EPFL)

Collaborations and Interactions:  M. Vetterli (EPFL),  M. Do  (UIUC). 

Department Home