Improvement of Grayscale Images in Orthogonal Basis of the Type-2 Membership Function
Lyudmila G. Akhmetshina, Artyom Yegorov · 2021
While analyzing different images, it is very important to identify similar and/or homogeneous areas and boundaries of the objects of interest.Certain ambiguity occurred at this step can be caused by physical characteristics of the used equipment and noise in the process of the image formation, on the one part, and by inaccuracy and fuzziness introduced during digital representation and by processing algorithms, on the other part.It is shown that transition of the features to a fuzzy space, followed by the use of orthogonal transformation and visualization of characteristics synthesized on the basis of their eigenvalues, improves reliability of the objects of interest identification during analyzing of the grayscale images.Informational capabilities of characteristics synthesized with the use of the method of singular decomposition of the type-2 features in a fuzzy space are considered from the aspect of improvement of the grayscale image quality.The obtained experimental results are shown on the example of the real microscopic images.