Tull, Damon L.

In the near future, digital television, enhanced cable and wireless services will give consumers and professionals unprecedented access to video data in digital format. These emerging technologies will create a demand for new, more sophisticated tools for the manipulation and enhancement of digital image sequences, across a broad range of imaging modalities.

My research focuses on the development of these tools -- algorithms and systems that address the inevitable problems that impede the efficient acquisition, representation, and transmission of digital image sequences. These problems are often difficult, ill-posed problems that lack a unique and stable solution. An aspect of my research considers special (robust) procedures required to transform an ill-posed problem into a well-posed one. I have considered the used of these techniques in a broad range of image sequence problems including:

Image restoration
Image and video compression (e.g. JPEG, MPEG)
Image synthesis
Image motion estimation and analysis

I am also interested in how constraints or cues from the human visual system impact the solution to these problems. My latest work shows that a special class of dynamic visual cues can be used successfully, in conjunction with robust statistical regularization, to obtain unique, meaningful solutions to the image restoration and motion estimation problems.

I am presently exploring new regularization techniques for ill-posed inverse problems, the efficient implementation of regularized iterative algorithms and intelligent/adaptive image acquisition systems.

Date last modified: 19-Aug-2011
Content by: tull@engr.wisc.edu
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