Abo Bibliothek: Guest
Digitales Portal Digitale Bibliothek eBooks Zeitschriften Referenzen und Berichte Forschungssammlungen
Telecommunications and Radio Engineering
SJR: 0.203 SNIP: 0.44 CiteScore™: 1

ISSN Druckformat: 0040-2508
ISSN Online: 1943-6009

Volumes:
Volumen 79, 2020 Volumen 78, 2019 Volumen 77, 2018 Volumen 76, 2017 Volumen 75, 2016 Volumen 74, 2015 Volumen 73, 2014 Volumen 72, 2013 Volumen 71, 2012 Volumen 70, 2011 Volumen 69, 2010 Volumen 68, 2009 Volumen 67, 2008 Volumen 66, 2007 Volumen 65, 2006 Volumen 64, 2005 Volumen 63, 2005 Volumen 62, 2004 Volumen 61, 2004 Volumen 60, 2003 Volumen 59, 2003 Volumen 58, 2002 Volumen 57, 2002 Volumen 56, 2001 Volumen 55, 2001 Volumen 54, 2000 Volumen 53, 1999 Volumen 52, 1998 Volumen 51, 1997

Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v68.i9.10
pages 747-761

Super-Resolution Method Based on Wavelet Atomic Functions in Images and Video Sequences

F. Gomeztagle
National Polytechnic Institute of Mexico, Mexico-city, Mexico
Victor Filippovich Kravchenko
Kotelnikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences, 11-7, Mokhovaya St., Moscow 125009, Russia; Bauman Moscow State Technical University, 5, Vtoraya Baumanskaya St., Moscow 105005 Russia; Scientific and Technological Center of Unique Instrumentation, Russian Academy of Sciences, 15, Butlerova St., Moscow 117342, Russia
Volodymyr Ponomaryov
Instituto Politécnico Nacional, Mexico-city, Mexico

ABSTRAKT

A novel method for super resolution in the grayscale images and video sequences is introduced. In difference with conventional approaches, where the procedures use small pixels spatial information in the vicinity around the positions of the interpolation, a new framework employs the spatial spectral properties of an image or sequence applying wavelet transform technique. Novel wavelets based on atomic functions, which are used here, have shown good properties of resolution by extension of an image size up to 4 times in comparison with the original low resolution image reconstructing three new pixels should be estimated for each one existing pixel. Numerous statistical simulations have demonstrated the effectiveness of the novel technique, exposing an excellent subjective visual quality, as well as significant improvement of super resolution image in terms of objective criteria in comparison with better existing algorithms.


Articles with similar content:

IMAGE RESOLUTION ENHANCEMENT USING EDGE EXTRACTION, SPARSE REPRESENTATION AND INTERPOLATION IN WAVELET DOMAIN
Telecommunications and Radio Engineering, Vol.72, 2013, issue 19
H. Chavez-Roman, Victor Filippovich Kravchenko, Gonzalo Duchen-Sanchez, Volodymyr Ponomaryov
DENOISING OF MULTICHANNEL IMAGES WITH NONLINEAR TRANSFORMATION OF REFERENCE IMAGE
Telecommunications and Radio Engineering, Vol.77, 2018, issue 9
V. V. Lukin, S. K. Abramov, Karen O. Egiazarian, V. V. Abramova
BIAS MINIMIZATION IN GAUSSIAN PROCESS SURROGATE MODELING FOR UNCERTAINTY QUANTIFICATION
International Journal for Uncertainty Quantification, Vol.1, 2011, issue 4
Vadiraj Hombal, Sankaran Mahadevan
PROPER ORTHOGONAL DECOMPOSITION ON COMPRESSED DATA
TSFP DIGITAL LIBRARY ONLINE, Vol.10, 2017, issue
Oana Marin, Elia Merzari, Andrew Siegel, Phillipp Schlatter
Improved Distributions of Densities of Pseudo Currents Obtained from Test Magnetic or Electropotential Images with Dipole Structure
Journal of Automation and Information Sciences, Vol.39, 2007, issue 11
Nikolay N. Budnyk, Vitaliy N. Budnyk