Εμφανίζονται 1 - 4 Αποτελέσματα από 4 για την αναζήτηση '"параметры фильтров"', χρόνος αναζήτησης: 0,52δλ Περιορισμός αποτελεσμάτων
  1. 1
    Academic Journal

    Συγγραφείς: Sliusarchuk, O. O.

    Πηγή: Visnyk NTUU KPI Seriia-Radiotekhnika Radioaparatobuduvannia; 77; 60-65
    Вісник НТУУ "КПІ". Серія Радіотехніка, Радіоапаратобудування; 77; 60-65
    Вестник НТУУ" КПИ ". Серия радиотехника Радиоаппаратостроение; 77; 60-65

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  2. 2
    Academic Journal

    Πηγή: Journal of the Russian Universities. Radioelectronics; Том 24, № 4 (2021); 6-18 ; Известия высших учебных заведений России. Радиоэлектроника; Том 24, № 4 (2021); 6-18 ; 2658-4794 ; 1993-8985

    Περιγραφή αρχείου: application/pdf

    Relation: https://re.eltech.ru/jour/article/view/537/550; Тузова А. А., Павлов В. А., Белов А. А. Применение платформы Jetson TX1 для реализации алгоритмов формирования радиолокационных изображений радиолокатора с синтезированной апертурой // Неделя науки СПбПУ 2019: материалы науч. конф. с международным участием. СПб.: Изд-во Политехн. ун-та, 2019. С. 26-29.; Pavlov V. A., Belov A. A., Tuzova A. A. Implementation of Synthetic Aperture Radar Processing Algorithms on the Jetson TX1 Platform // IEEE Intern. Conf. on Electrical Engineering and Photonics (EExPolytech), St Petersburg, 2019. P. 90-93. doi:10.1109/EExPolytech.2019.8906850; Волков В. Ю. Адаптивное выделение мелких объектов на цифровых изображениях // Изв. вузов России. Радиоэлектроника. 2017. № 1. С. 17-28.; Fursov V., Zherdev D., Kazanskiy N. Support subspaces method for synthetic aperture radar automatic target recognition // Intern. J. of Advanced Robotic Systems. 2016. Vol. 13, iss. 5. P. 1-11. doi:10.1177/1729881416664848; Domg Y., Milne A. K., Forster B. C. Toward edge sharpening: a SAR speckle filtering algorithm // IEEE Transactions on Geoscience and Remote Sensing. Apr. 2001. Vol. 39, № 4. P. 851-863. doi:10.1109/36.917910; Yongjian Yu., Acton S. T. Speckle reducing anisotropic diffusion // IEEE Transactions on Image Processing. 2002. Vol. 11, № 11. P. 1260-1270. doi:10.1109/TIP.2002.804276; A New Image Quality Index for Objectively Evaluating Despeckling Filtering in SAR Images / L. Gomez, M. E. Buemi, J. C. Jacobo-Berlles, M. E. Mejail // IEEE J. of Selected Topics in Applied Earth Observations and Remote Sensing. 2016. Vol. 9, № 3. P. 1297-1307. doi:10.1109/JSTARS.2015.2465167; Speckle Reduction of Reconstructions of Digital Holograms Using Gamma-Correction and Filtering / X. Huang, Z. Jia, J. Zhou, J. Yang, N. Kasabov // IEEE Access. 2018. Vol. 6. P. 5227-5235. doi:10.1109/ACCESS.2017.2751540; Старовойтов В. В. Методика выбора фильтра для сглаживания спекл-шума радарных изображений с синтезированной апертурой // Информатика. 2015. № 2. Р. 5-11.; Исследование методов удаления спекл-шумов на ультразвуковых изображениях / А. Бобкова, С. Поршнев, В. Зюзин, В. Бобков // The 23rd Intern. Conf. on Computer Graphics and Vision, Vladivostok, Sept. 2013. P. 244-246.; Touzi R. A review of speckle filtering in the context of estimation theory // IEEE Transactions on Geoscience and Remote Sensing. 2002. Vol. 40, iss. 11. P. 2392-2404. doi:10.1109/TGRS.2002.803727; Aja-Fernandez S., Alberola-Lopez C. On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering // IEEE Transactions on Image Processing. 2006. Vol. 15, № 9. P. 2694-2701. doi:10.1109/TIP.2006.877360; Oriented Speckle Reducing Anisotropic Diffusion / K. Krissian, C. Westin, R. Kikinis, K. G. Vosburgh // IEEE Transactions on Image Processing. 2007. Vol. 16, № 5. P. 1412-1424. doi:10.1109/TIP.2007.891803; Improved Sigma Filter for Speckle Filtering of SAR Imagery / Jong-Sen Lee, Jen-Hung Wen, T. L. Ainsworth, Kun-Shan Chen, A. J. Chen // IEEE Transactions on Geoscience and Remote Sensing. 2009. Vol. 47, № 1. P. 202-213. doi:10.1109/TGRS.2008.2002881; FPGA-Based Adaptive Speckle Suppression Filter for Underwater Imaging Sonar / S. Karabchevsky, D. Kahana, O. Ben-Harush, H. Guterman // IEEE J. of Oceanic Engineering. 2011. Vol. 36, № 4. P. 646-657. doi:10.1109/JOE.2011.2157729; Spatial filtering strategies on deforestation detection using SAR image textures / X. Dong, D. Zhang, K. Cui, C. Hu, X. Lv // CIE Intern. Conf. on Radar (RADAR), Guangzhou, China, 2016. P. 1-4. doi:10.1109/RADAR.2016.8059472; Anisotropic Diffusion Filter With Memory Based on Speckle Statistics for Ultrasound Images / G. RamosLlordén, G. Vegas-Sánchez-Ferrero, M. Martin-Fernandez, C. Alberola-López, S. Aja-Fernández // IEEE Transactions on Image Processing. 2015. Vol. 24, № 1. P. 345-358. doi:10.1109/TIP.2014.2371244; Paul A., Mukherjee D. P., Acton S. T. Speckle Removal Using Diffusion Potential for Optical Coherence Tomography Images // IEEE J Biomed Health Inform. 2019. Vol. 23, iss. 1. P. 264-272. doi:10.1109/JBHI.2018.2791624; Gonzalez R. C., Woods R. E. Digital Image Processing. 2nd ed. Addison-Wesley Longman Publishing Co., Inc., USA, New Jersey 07458, 2001. 191 p.; Lee Jong-Sen Digital Image Enhancement and Noise Filtering by Use of Local Statistics // IEEE Transactions on Pattern Analysis and Machine Intelligence. 1980. Vol. PAMI-2, № 2. P. 165-168. doi:10.1109/TPAMI.1980.4766994; A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise / V. S. Frost, J. A. Stiles, K. S. Shanmugan, J. C. Holtzman // IEEE Transactions on Pattern Analysis and Machine Intelligence. 1982. Vol. PAMI-4, № 2. P. 157-166. doi:10.1109/TPAMI.1982.4767223; Adaptive restoration of images with speckle / D. Kuan, A. Sawchuk, T. Strand, P. Chavel // IEEE Transactions on Acoustics, Speech and Signal Processing. 1987. Vol. 35, № 3. P. 373-383. doi:10.1109/TASSP.1987.1165131; Tomasi C., Manduchi R. Bilateral filtering for gray and color images // Sixth Intern. Conf. on Computer Vision (IEEE Cat. No.98CH36271), Bombay, India, 1998. P. 839-846. doi:10.1109/ICCV.1998.710815; Structure detection and statistical adaptive speckle filtering in SAR images / A. Lopes, E. Nezry, R. Touzi, H. Laur // Intern. J. of Remote Sensing. 1993. Vol. 14, iss. 9. P. 1735-1758. doi:10.1080/01431169308953999; Perona P., Malik J. Scale-space and edge detection using anisotropic diffusion // IEEE Transactions on Pattern Analysis and Machine Intelligence. 1990. Vol. 12, iss. 7. P. 629-639. doi:10.1109/34.56205; Image quality assessment: From error visibility to structural similarity / Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli // IEEE Transactions on Image Processing. 2004. Vol. 13, iss. 4. P. 600–612. doi:10.1109/TIP.2003.819861; Wang Z., Bovik A. C. A universal image quality index // IEEE Signal Processing Lett. 2002. Vol. 9, iss. 3. P. 81–84. doi:10.1109/97.995823; Gradient magnitude similarity deviation: A highly efficient perceptual image quality index / W. Xue, L. Zhang, X. Mou, A. C. Bovik // IEEE Transactions on Image Processing. 2014. Vol. 23, iss. 2. P. 684–695. doi:10.1109/TIP.2013.2293423; Comparison of Image Quality Assessment Metrics for Evaluation of Performance of Anisotropic Diffusion Filter for SAR Images / A. A. Tuzova, V. A. Pavlov, A. A. Belov, S. V. Volvenko // IEEE Intern. Conf. on Electrical Engineering and Photonics (EExPolytech), St Petersburg, 2020. P. 176-179. doi:10.1109/EExPolytech50912.2020.9243957; Methods for Blind Estimation of Speckle Variance in SAR Images: Simulation Results and Verification for Real-Life Data / S. Abramov, V. Abramova, V. Lukin, N. Ponomarenko, B. Vozel, K. Chehdi, K. Egiazarian, Ja. Astol // Computational and Numerical Simulations. 2014. Ch. 24. P. 303-327. doi:10.5772/57040; Choi H., Jeong J. Speckle noise reduction technique for SAR images using statistical characteristics of speckle noise and discrete wavelet transform // Remote Sensing, 2019. Vol. 11, iss. 1184. P. 1-27. doi:10.3390/rs11101184; Xie Hua, Pierce L. E., Ulaby F. T. Statistical properties of logarithmically transformed speckle // IEEE Transactions on Geoscience and Remote Sensing. 2002. Vol. 40, iss. 3. P. 721-727. doi:10.1109/TGRS.2002.1000333; Singh P., Pandey R. Speckle noise: Modelling and implementation // Intern. J. of Circuit Theory and Applications. 2016. Vol. 9, iss. 17. P. 8717–8727.; Herman C., Lehmann E. L. The use of maximum likelihood estimates in χ2 tests for goodness of fit // Ann. Math. Statist. 1954. Vol. 25, iss. 3. P. 579-586. doi:10.1214/aoms/1177728726; Pearson K. On the criterion that a given system of deviations from theprobable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling // Breakthroughs in Statistics: Methodology and Distribution / eds. S. Kotz, N. L. Johnson. New York: Springer New York, 1992. P. 11–28. doi:10.1007/978-1-4612-4380-9_2; Belov A. A., Pavlov V. A., Tuzova A. A. A Method of Finding Optimal Parameters of Speckle Noise Reduction Filters // Internet of Things, Smart Spaces and Next Generation Networks and Systems, Springer Intern. Publishing, 2020. P. 133-141. doi:10.1007/978-3-030-65729-1_12; Тузова А. А. Проект по поиску оптимальных параметров фильтров спекл-шума. Файл FilteringSpeckleNoise_main_script.m. URL: https://github.com/AnnaTuzova/Speckle-noise-project (дата обращения 25.04.2021); https://re.eltech.ru/jour/article/view/537

  3. 3
    Academic Journal

    Relation: Journal of Siberian Federal University. Engineering & Technologies 2023; Журнал Сибирского федерального университета. 2023 16 (7); HXUATR

    Διαθεσιμότητα: https://elib.sfu-kras.ru/handle/2311/151839

  4. 4
    Academic Journal

    Relation: Журнал Сибирского федерального университета. Техника и технологии. Journal of Siberian Federal University. Engineering & Technologies 2021 14(3)