Abstract
Postprocessing of reconstructed images becomes is a means to enhance the visibility of reconstructed images. Image processing, enhancement, and restoration methods are widely available for use with digital photographs, video frames, and astronomical images. This chapter gives an overview of image enhancement methods, addressed in a fashion similar to that used for solving the inverse problem of image reconstruction. Direct image enhancement is concerned with removing spatial blurring and faintness, in order to provide the human eye with appealing crisper and sharper images. It aims at producing a better quality image from an image of lesser quality. It is, therefore, a mapping of one image to another. It can be viewed as an inverse problem for which the input is the raw image. This mapping is, however, a one-to-one correspondence between the pixel/ voxels of the enhanced image and those of the raw image; unlike the inverse problem of image reconstruction where a measurement usually corresponds to many image parameters. As a result, the inverse problem of image enhancement deals with pixels/ voxels that are not directly correlated to each other. On the other hand, because in image reconstruction measurements present some form of correlation between pixels/ voxels, it is advisable to incorporate some image enhancement measures within the image reconstruction process itself through regularization.
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