Information technology for low-contrast image processing in the space of ellipsometric stokes parameters
DOI:
https://doi.org/10.15587/1729-4061.2014.27667Keywords:
low-contrast image, ellipsometric characteristics, modulation conversion, normalization, orthogonalization, singular value decompositionAbstract
A method for low-contrast image processing and analysis in the space of ellipsometric Stokes parameters, which can be applied to improve the quality of one-parameter and multi-parameter images is proposed in the paper. Under the method, each pixel of the analyzed image is compared with four virtual Stokes parameters, which allows naturally implement color RGB coding of results without using the pseudocolor coding procedure. The proposed results interpretation method using RGB coding based on the parameters improves the low-contrast image analysis reliability.
Experiments have shown that the most appropriate method for multispectral ensemble compression is a singular value decomposition method. Images, corresponding to the first three maximum singular values are taken as three main (“own”) images. The synthesis of elliptic characteristics based on their “own” images provides a higher degree of detail of the resulting color elliptic RGB coding compared with direct RGB coding of three “own” images.
Presented information technology allows to carry out low-contrast image processing using the described methods and is designed to increase the sensitivity of visual analysis and selection of objects of potential interest.References
Shovengerdt, R. A. (2010). Distancionnoe zondirovanie. Modeli i metody obrabotki izobrazhenij. Moscow: Tehnosferab, 560.
Kalender, V. A. (2006). Komp'juternaja tomografija. Osnovy, tehnika, kachestvo izobrazhenij i oblasti klinicheskogo ispol'zovanija. Moscow: Tehnosfera, 334.
Gonsales, R., Vuds, R. (2006). Cifrovaja obrabotka izobrazhenij. Moscow: Tehnosfera, 1070.
Jane, B. (2007). Cifrovaja obrabotka izobrazhenij. Moscow: Tehnosvera, 583.
Forsajt, D., Pons, Zh. (2004). Komp'juternoe zrenie: sovremennyj podhod. Moscow; SPb.; Kiev: Vil'jams, 926.
Kinoshenko, D., Mashtalir, V., Yegorova, E., Shlyakhov, V.; Wei, C.-H. Li, Y. (Ed.) (2010). Metrical Properties of Nested Partitions for Image Retrieval. Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives, 18–49.
Kondrat'ev, A. A., Tishhenko, I. P. (2012). Ispol'zovanie graficheskih vychislitelej v processah obrabotki i raspoznavanija izobrazhenij. Aktual'nye problemy raketno-kosmicheskogo priborostroenija i informacionnyh tehnologij». Mosow: Radiotehnika, 92.
Staren'kij, V. P., Aver'janova, L. A., Vasil'ev, L. L. (2012). Primenenie metodov konturnoj segmentacii tomogramm dlja usovershenstvovanija topometricheskoj podgotovki konformnoj luchevoj terapii. Vestnik NTU «HPI». Serija: Informatika i modelirovanie, 62 (968), 194–199.
Abakumov, V. G., Antoshhuk, S. G., Krylov, V. N. (2008). Bazovye metody obrabotki biomedicinskih zobrazhenij. Jelektronika i svjaz', Part 2, 53–58.
Udovik, I. M., Ahmetshina, L. G., Ahmetshin, A. M. (2010). Samoorganizujushhijsja interferencionnyj metod segmentacii slabokontrastnyh izobrazhenij. Iskusstvennyj intellekt, 3, 427–431.
Ahmetshina, L. G., Udovik, I. M. (2011). Fazovaja segmentacija mul'tispektral'nyh slabokontrastnyh izobrazhenij. Iskusstvennyj intellekt, 3, 200–206.
Udovik, I. M. (2011). Samoorganizujushhijsja interferencionnyj metod fazovoj segmentacii mul'tispektral'nyh izobrazhenij. Informacionnye tehnologii i bezopasnost' v nauke, tehnike i obrazovanii INFOTEH-2011. Sevastopol', 164.
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Copyright (c) 2014 Ирина Михайловна Удовик
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