ABSTRACT
In all cases, it should be understood that enhancement is a two-edged sword. Making the details of interest more visible is accomplished by making other information in the image less visible. This implies a decision about which details are important, and that depends on the context in which the image is being used. As a very simple example, the random speckle noise within uniform features in an image, which can be reduced or eliminated using the methods described in the preceding chapter, is undesirable for purposes of viewing the image, and measuring the dimensions or mean intensity of the region. Eliminating it would be considered a form of enhancement. On the other hand, the amplitude of the noise contains information about the imaging process, the illumination intensity and the camera response. That information might be important if it was needed to verify the conditions under which the image was acquired, or to compare that image to others purported to be similar. Eliminating the noise eliminates the information. Similarly, most processes that alter pixel values to make the differences within the image more visible also destroy any calibration relationship between the pixel values and sample density.
