The ``index of fuzziness'' and ``entropy'' of an image reflect a kind of quantitative measure of its enhancement quality. Their values are found to decrease with enhancement of an image when different sets of S-type membership functions with appropriate crossover points were considered for extracting the fuzzy property plane from the spatial domain of the image.
The necessity of determining to what degree the possession of specific elementary properties, by an object, can be evinced from other properties of more complex structure, represents a problem which may arise in fuzzy classification of objects. In this paper, the possibility that said elementary properties are describable through strings of words, and that these last singly denote either the presence or the absence, in each object, of an atomic property is assumed. Also an algorithm by means of which those atomic properties which in the performed descriptions are relevant is presented. Such an algorithm is based on the morphosyntactical mechanisms forming the (transformational-generative) grammar of the language by which said description are performed. The mathematical relevance of the subject treated in the paper is relative to the developed type of transformation of formal descriptions. The codification of this constitutes, in fact, the accomplishment of an essential phase toward the quantitative evaluation of the fuzziness of the descriptions and, consequently, of their significance.
Ultrasound/tissue interactions provide a fertile base for imaging techniques, and a number of novel and apparently diverse methods for human imaging are currently being developed. An original, unified theory of these quantitative scatter-imaging techniques is developed. It is demonstrated that the success of the methods is inextricably bound together with the development of physical models for the ultrasound/tissue interaction. The concept of image 'fuzziness' is introduced and contrasted against attained image resolution.