Noise reduction is an important step for development of any
sophisticated algorithms in computer vision and image processing. A
tradeoff between the removed noise and the blur in the image always
exists. The capability of the wavelets to give detail
spatial-frequency information is the main reason for the use of
wavelets. This property promises a possibility for better
discrimination between the noise and the real data. Successful
exploitation of the wavelet transform might reduce the blurring
effect or even overcome it completely. Object tracking is a problem
of estimating the positions and other relevant information of
moving objects in the sequences of image video. The main
difficulties in reliable tracking of moving objects include: rapid
appearance changes caused by image noise and interaction between
multiple objects. In a long sequence of image video, if the
dynamics of the moving object is known, prediction can be made
about the positions of the object in a particular frame. This
information can be combined with the actual image observation to
achieve more robust results. We have explored a possibility to use
wavelet transform for object tracking.
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