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Найдено документов в текущей БД: 2

    Image compression algorithm using wavelet transform
/ L. Cadena [et al.] // Proceedings of SPIE - The International Society for Optical Engineering : SPIE, 2016. - Vol. 9971: Applications of Digital Image Processing XXXIX (29 August 2016 through 1 September 2016, ) Conference code: 125275, DOI 10.1117/12.2235583 . -
Аннотация: Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the variation of the compression level of the studied image has been obtained. It is shown that the compression ratio in the range of 8-10 is optimal for environmental monitoring. Under these conditions the compression level is in the range of 1.7-4.2, depending on the type of images. It is shown that the algorithm used is more convenient and has more advantages than Winrar. The Haar wavelet algorithm has improved the method of signal and image processing. © 2016 SPIE.

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Держатели документа:
Universidad de las Fuerzas Armadas ESPE, Av. Gral Ruminahui s/n, Sangolqui, Ecuador
Colegio Juan Suarez Chacon, Quito, Ecuador
Institute of Computational Modelling, SB RAN, 50/44 Akademgorodok str., Krasnoyarsk, Russian Federation
Siberian State Aerospace University, 31 krasnoyarsky rabocho pr., Krasnoyarsk, Russian Federation
Saint Petersburg State University, Universitetskaya Embankment 7-9, St.-Petersburg, Russian Federation

Доп.точки доступа:
Cadena, L.; Cadena, F.; Simonov, K.; Zotin, A.; Okhotnikov, G.
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    Diagnostics of Complex Phenomena on the Basis of Geometrical Analysis Images
/ L. Cadena [et al.] // Lecture Notes in Engineering and Computer Science : Newswood Limited, 2017. - Vol. 2227: 2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017 (15 March 2017 through 17 March 2017, ) Conference code: 133365. - P401-404 . -

Кл.слова (ненормированные):
Analysis of medical images -- Contour -- Denoising -- Image processing -- Medical image -- Shearlet -- Ureteroscopy -- Urolithiasis -- Wavelets -- Diagnosis -- Geometry -- Image processing -- Medical imaging -- Contour -- De-noising -- Shearlet -- Ureteroscopy -- Urolithiasis -- Wavelets -- Image analysis

Аннотация: A review of the basic concepts shearlet transform spatial data observations. The possibilities of the new approach for the geometric analysis of complex medical images. The proposed method can improve the radiological diagnosis of urological diseases by detailing changes of tissues. On the basis of the developed method of spectral data decomposition is performed solution of filtration problem and isolating contour studied medical target. The task of image contrast is also solved for the better understanding of the found geometric features and patterns.

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Держатели документа:
Electric and Electronic Department, Universidad de las Fuerzas Armadas ESPE, Av. Gral Ruminahui s/n, Sangolqui, Ecuador
College Juan Suarez Chacon, Quito, Ecuador
Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, Russian Federation
Institute of Computational Modelling, Siberian Branch, Russian Academy of Science, 50/44 Akademgorodok str., Krasnoyarsk, Russian Federation
Krasnoyarsk State Medical University, 1 Partizana Geleznyaka str., Krasnoyarsk, Russian Federation

Доп.точки доступа:
Cadena, L.; Cadena, F.; Kruglyakov, A.; Simonov, K.; Kapsargin, F.
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