ABSTRACT
The influence of various types of noise in biomedical images can not be fully eliminated at the time of image acquisition. This chapter shows how wavelet-based postprocessing methods can be applied to reduce such measurement noise. Noise suppression methods can indeed take full advantage of the localization in both space and frequency that is offered by the wavelet transform. By using this localization, wavelet-based methods can avoid the typical smoothing of fine features that occurs with other methods. The chapter includes an overview of wavelet-based methods that can be used for noise suppression, with the emphasis on methods that are based on a manipulation of the wavelet coefficients. We describe a particular approach that is capable of suppressing most of the noise, while maintaining the relevant fine features in the processed image, which is important for biomedical images. This is illustrated with results for several biomedical images.
