ABSTRACT
Image restoration methods are used to improve the appearance of an image by application of a restoration process that uses a mathematical model for image degradation. Examples of the types of degradation considered include additive noise, blurring caused by motion or atmospheric disturbance, geometric distortion caused by imperfect lenses and superimposed interference patterns caused by mechanical systems. The degradation model is known or estimated and the inverse degradation process model is applied to restore the original image. A system model is included for algorithm development and methods to estimate the degradation process. The types of degradation that can be modeled, and techniques available in both the spatial and frequency domains are discussed. Noise models and degradation functions in both domains are introduced – the point spread function and the modulation transfer function. Noise removal with order, mean and adaptive spatial filters are included. Frequency domain restoration filters including the inverse, the Wiener and many types of geometric filters are discussed, including practical considerations. Adaptive filters, bandpass, bandreject and notch filters are included. Equations and examples are provided. The final section in this chapter deals with image reconstruction, which is a method to create an image from a sequence of projections. Along with the text are 58 illustrative figures and 138 associated monochrome and color images. The end of chapter exercises include problems and programming exercises.
