Matches in SemOpenAlex for { <https://semopenalex.org/work/W2014693452> ?p ?o ?g. }
- W2014693452 endingPage "2033" @default.
- W2014693452 startingPage "2018" @default.
- W2014693452 abstract "Image up-sampling in the discrete cosine transform (DCT) domain is a challenging problem because DCT coefficients are de-correlated, such that it is nontrivial to estimate directly high-frequency DCT coefficients from observed low-frequency DCT coefficients. In the literature, DCT-based up-sampling algorithms usually pad zeros as high-frequency DCT coefficients or estimate such coefficients with limited success mainly due to the nonadaptive estimator and restricted information from a single observed image. In this paper, we tackle the problem of estimating high-frequency DCT coefficients in the spatial domain by proposing a learning-based scheme using an adaptive k-nearest neighbor weighted minimum mean squares error (MMSE) estimation framework. Our proposed scheme makes use of the information from precomputed dictionaries to formulate an adaptive linear MMSE estimator for each DCT block. The scheme is able to estimate high-frequency DCT coefficients with very successful results. Experimental results show that the proposed up-sampling scheme produces the minimal ringing and blocking effects, and significantly better results compared with the state-of-the-art algorithms in terms of peak signal-to-noise ratio (more than 1 dB), structural similarity, and subjective quality measurements." @default.
- W2014693452 created "2016-06-24" @default.
- W2014693452 creator A5077009206 @default.
- W2014693452 creator A5083042979 @default.
- W2014693452 date "2014-12-01" @default.
- W2014693452 modified "2023-10-16" @default.
- W2014693452 title "Novel DCT-Based Image Up-Sampling Using Learning-Based Adaptive k-NN MMSE Estimation" @default.
- W2014693452 cites W1948356912 @default.
- W2014693452 cites W1969056174 @default.
- W2014693452 cites W1976640676 @default.
- W2014693452 cites W1977581467 @default.
- W2014693452 cites W1981199328 @default.
- W2014693452 cites W1982753412 @default.
- W2014693452 cites W1989510016 @default.
- W2014693452 cites W2015607400 @default.
- W2014693452 cites W2016598597 @default.
- W2014693452 cites W2019273241 @default.
- W2014693452 cites W2023310246 @default.
- W2014693452 cites W2024647105 @default.
- W2014693452 cites W2035285952 @default.
- W2014693452 cites W2042127890 @default.
- W2014693452 cites W2044459029 @default.
- W2014693452 cites W2062378984 @default.
- W2014693452 cites W2070501385 @default.
- W2014693452 cites W2080875060 @default.
- W2014693452 cites W2082546382 @default.
- W2014693452 cites W2087380704 @default.
- W2014693452 cites W2097074225 @default.
- W2014693452 cites W2099001916 @default.
- W2014693452 cites W2099803555 @default.
- W2014693452 cites W2102226020 @default.
- W2014693452 cites W2102498100 @default.
- W2014693452 cites W2106692341 @default.
- W2014693452 cites W2106913527 @default.
- W2014693452 cites W2109263915 @default.
- W2014693452 cites W2109773745 @default.
- W2014693452 cites W2113350594 @default.
- W2014693452 cites W2117364864 @default.
- W2014693452 cites W2122726909 @default.
- W2014693452 cites W2124252144 @default.
- W2014693452 cites W2131724888 @default.
- W2014693452 cites W2133665775 @default.
- W2014693452 cites W2134400176 @default.
- W2014693452 cites W2134427032 @default.
- W2014693452 cites W2136313643 @default.
- W2014693452 cites W2137160452 @default.
- W2014693452 cites W2139531323 @default.
- W2014693452 cites W2143797118 @default.
- W2014693452 cites W2144593004 @default.
- W2014693452 cites W2147185237 @default.
- W2014693452 cites W2153537702 @default.
- W2014693452 cites W2154666954 @default.
- W2014693452 cites W2156559424 @default.
- W2014693452 cites W2161112041 @default.
- W2014693452 cites W2167343587 @default.
- W2014693452 cites W2167789654 @default.
- W2014693452 cites W2169314156 @default.
- W2014693452 cites W2170386820 @default.
- W2014693452 cites W2170794878 @default.
- W2014693452 cites W2170965888 @default.
- W2014693452 cites W3104720471 @default.
- W2014693452 doi "https://doi.org/10.1109/tcsvt.2014.2329352" @default.
- W2014693452 hasPublicationYear "2014" @default.
- W2014693452 type Work @default.
- W2014693452 sameAs 2014693452 @default.
- W2014693452 citedByCount "20" @default.
- W2014693452 countsByYear W20146934522014 @default.
- W2014693452 countsByYear W20146934522015 @default.
- W2014693452 countsByYear W20146934522016 @default.
- W2014693452 countsByYear W20146934522017 @default.
- W2014693452 countsByYear W20146934522018 @default.
- W2014693452 countsByYear W20146934522019 @default.
- W2014693452 countsByYear W20146934522021 @default.
- W2014693452 countsByYear W20146934522022 @default.
- W2014693452 crossrefType "journal-article" @default.
- W2014693452 hasAuthorship W2014693452A5077009206 @default.
- W2014693452 hasAuthorship W2014693452A5083042979 @default.
- W2014693452 hasConcept C105795698 @default.
- W2014693452 hasConcept C106131492 @default.
- W2014693452 hasConcept C11413529 @default.
- W2014693452 hasConcept C115961682 @default.
- W2014693452 hasConcept C134306372 @default.
- W2014693452 hasConcept C13481523 @default.
- W2014693452 hasConcept C139945424 @default.
- W2014693452 hasConcept C153180895 @default.
- W2014693452 hasConcept C154579607 @default.
- W2014693452 hasConcept C154945302 @default.
- W2014693452 hasConcept C17828673 @default.
- W2014693452 hasConcept C185429906 @default.
- W2014693452 hasConcept C19118579 @default.
- W2014693452 hasConcept C2221639 @default.
- W2014693452 hasConcept C30684385 @default.
- W2014693452 hasConcept C31972630 @default.
- W2014693452 hasConcept C33923547 @default.
- W2014693452 hasConcept C41008148 @default.
- W2014693452 hasConcept C5317259 @default.
- W2014693452 hasConcept C9417928 @default.
- W2014693452 hasConceptScore W2014693452C105795698 @default.