4 - Medical Image Enhancement with Hybrid Filters

Abstract

Image enhancement is usually performed by either suppressing the noise or increasing the image contrast. The goal of enhancement techniques is to accentuate certain image features for subsequent analysis or display. Their properties should be noise reduction, detail preservation, and artifact-free images. In the early development of signal and image processing, the primary tools were linear filters. Their mathematical simplicity and the existence of some desirable properties made them easy to design and implement. In addition, various criteria such as the maximum entropy criterion lead to nonlinear solutions. In image processing applications, linear filters tend to blur the edges, do not remove impulsive noise effectively, and do not perform well in the presence of signal-dependent noise. Although the exact characteristics of our visual system are not well understood, experimental results indicate that the first processing levels of our visual system possess nonlinear characteristics. Nonlinear filtering has had a dynamic development since then. This is indicated by the amount of research published and the widespread use of nonlinear digital filters in a variety of applications, notably in telecommunications, image processing, and geophysical signal processing. The chapter presents the design of a hybrid filter combining an adaptive multistage nonlinear filter and a multiresolution/multiorientation wavelet transform. It also illustrates the application of the hybrid filter for image enhancement in medical imaging is illustrated.