Title :
An edge extraction technique for noisy images
Author :
Cios, Krzysztof J. ; Sarieh, Ayman
Author_Institution :
Toledo Univ., OH, USA
fDate :
5/1/1990 12:00:00 AM
Abstract :
An algorithm for extracting edges from noisy images is presented. The method uses an unsupervised learning approach for local threshold computation by means of K. Pearson´s (1984) method for mixture density identification. The technique was tested by applying it to computer-generated images corrupted with artificial noise and to an actual thallium-201 heart image, and it is shown that the technique has potential use for noisy images.
Keywords :
computerised picture processing; noise; radioisotope scanning and imaging; /sup 201/Tl heart image; artificial noise; computer-generated images; edge extraction algorithm; edge extraction technique; local threshold computation; mixture density identification; noisy images; unsupervised learning approach; Biomedical computing; Equations; Heart; Histograms; Image generation; Moment methods; Noise generators; Testing; Unsupervised learning; Working environment noise; Algorithms; Computer Systems; Heart; Humans; Image Processing, Computer-Assisted; Thallium Radioisotopes;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
