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Title Enhancement of low quality degraded video using haar wavelet decomposition technique
Authors Gupta, P.
Gadicha, V.B.
ORCID
Keywords haar wavelet
video enhancemnet
frame rate
mean intensity
Type Conference Papers
Date of Issue 2017
URI http://essuir.sumdu.edu.ua/handle/123456789/55756
Publisher Sumy State University
License
Citation Gupta, P. Enhancement of low quality degraded video using haar wavelet decomposition technique [Текст] / P. Gupta, V.B.Gadicha // Advanced Information Systems and Technologies : proceedings of the V international scientific conference, Sumy, May 17-19 2017/ Edited by S.І. Protsenko, V.V. Shendryk. - Sumy : Sumy State University, 2017. - P. 62-65.
Abstract The point recommends the general system for video improvement, object location and following continue at the same time in an aggressive and helpful way .Video is a gathering of successive pictures with a consistent time interim. So video can give more data about the article when situations are changing regarding time. Thusly, physically taking care of recordings are entirely unimaginable. So there is need of a computerized gadget to handle these recordings. Numerous calculations and innovation have been created to robotize video improvement and checking the article in a video document. Video improvement with item identification and following is a one of the testing errand in PC vision. Additionally, following of an article essentially includes two going before steps object identification and item representation. Object discovery is performed to check presence of items in video and to correctly find that article .Object following is a procedure of dividing a district of enthusiasm from a video scene and monitoring its movement, position and impediment. The following is performed by observing articles' spatial and transient changes amid a video grouping, including its nearness, position, size, shape, and so forth. Video improvement with article following is utilized as a part of a few applications, for example, video reconnaissance, robot vision, movement observing.
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