Matches in SemOpenAlex for { <https://semopenalex.org/work/W3183885280> ?p ?o ?g. }
- W3183885280 endingPage "2888" @default.
- W3183885280 startingPage "2888" @default.
- W3183885280 abstract "The imperfections of image acquisition systems produce noise. The majority of edge detectors, including gradient-based edge detectors, are sensitive to noise. To reduce this sensitivity, the first step of some edge detectors’ algorithms, such as the Canny’s edge detector, is the filtering of acquired images with a Gaussian filter. We show experimentally that this filtering is not sufficient in case of strong Additive White Gaussian or multiplicative speckle noise, because the remaining grains of noise produce false edges. The aim of this paper is to improve edge detection robustness against Gaussian and speckle noise by preceding the Canny’s edge detector with a new type of denoising system. We propose a two-stage denoising system acting in the Hyperanalytic Wavelet Transform Domain. The results obtained in applying the proposed edge detection method outperform state-of-the-art edge detection results from the literature." @default.
- W3183885280 created "2021-08-02" @default.
- W3183885280 creator A5009301093 @default.
- W3183885280 creator A5039349144 @default.
- W3183885280 creator A5045316602 @default.
- W3183885280 date "2021-07-23" @default.
- W3183885280 modified "2023-10-16" @default.
- W3183885280 title "Hyperanalytic Wavelet-Based Robust Edge Detection" @default.
- W3183885280 cites W1517207589 @default.
- W3183885280 cites W1592548556 @default.
- W3183885280 cites W1595114968 @default.
- W3183885280 cites W1977280446 @default.
- W3183885280 cites W1979904234 @default.
- W3183885280 cites W1990773344 @default.
- W3183885280 cites W2003370853 @default.
- W3183885280 cites W2004376198 @default.
- W3183885280 cites W2007203285 @default.
- W3183885280 cites W2008764442 @default.
- W3183885280 cites W2020880265 @default.
- W3183885280 cites W2028727259 @default.
- W3183885280 cites W2036524212 @default.
- W3183885280 cites W2038457848 @default.
- W3183885280 cites W2044927958 @default.
- W3183885280 cites W2049909233 @default.
- W3183885280 cites W2054457389 @default.
- W3183885280 cites W2072292891 @default.
- W3183885280 cites W2094178934 @default.
- W3183885280 cites W2096011446 @default.
- W3183885280 cites W2106219791 @default.
- W3183885280 cites W2117294245 @default.
- W3183885280 cites W2120729642 @default.
- W3183885280 cites W2129553449 @default.
- W3183885280 cites W2130219601 @default.
- W3183885280 cites W2130829856 @default.
- W3183885280 cites W2130836991 @default.
- W3183885280 cites W2137584359 @default.
- W3183885280 cites W2137985815 @default.
- W3183885280 cites W2145023731 @default.
- W3183885280 cites W2146361563 @default.
- W3183885280 cites W2147176572 @default.
- W3183885280 cites W2147297997 @default.
- W3183885280 cites W2158940042 @default.
- W3183885280 cites W2159509402 @default.
- W3183885280 cites W2161882007 @default.
- W3183885280 cites W2164611927 @default.
- W3183885280 cites W2164809340 @default.
- W3183885280 cites W2168815453 @default.
- W3183885280 cites W2170885533 @default.
- W3183885280 cites W2330056217 @default.
- W3183885280 cites W2475735051 @default.
- W3183885280 cites W2508457857 @default.
- W3183885280 cites W2562002910 @default.
- W3183885280 cites W2673969421 @default.
- W3183885280 cites W2751108875 @default.
- W3183885280 cites W2794233697 @default.
- W3183885280 cites W2883888661 @default.
- W3183885280 cites W2886849145 @default.
- W3183885280 cites W2905223677 @default.
- W3183885280 cites W2954537798 @default.
- W3183885280 cites W2959574828 @default.
- W3183885280 cites W3013302728 @default.
- W3183885280 cites W3025007558 @default.
- W3183885280 cites W3105425562 @default.
- W3183885280 cites W3128476715 @default.
- W3183885280 cites W3158709967 @default.
- W3183885280 cites W4302067267 @default.
- W3183885280 cites W4377938732 @default.
- W3183885280 doi "https://doi.org/10.3390/rs13152888" @default.
- W3183885280 hasPublicationYear "2021" @default.
- W3183885280 type Work @default.
- W3183885280 sameAs 3183885280 @default.
- W3183885280 citedByCount "6" @default.
- W3183885280 countsByYear W31838852802021 @default.
- W3183885280 countsByYear W31838852802022 @default.
- W3183885280 countsByYear W31838852802023 @default.
- W3183885280 crossrefType "journal-article" @default.
- W3183885280 hasAuthorship W3183885280A5009301093 @default.
- W3183885280 hasAuthorship W3183885280A5039349144 @default.
- W3183885280 hasAuthorship W3183885280A5045316602 @default.
- W3183885280 hasBestOaLocation W31838852801 @default.
- W3183885280 hasConcept C102290492 @default.
- W3183885280 hasConcept C115961682 @default.
- W3183885280 hasConcept C14705441 @default.
- W3183885280 hasConcept C153180895 @default.
- W3183885280 hasConcept C154945302 @default.
- W3183885280 hasConcept C163294075 @default.
- W3183885280 hasConcept C167074055 @default.
- W3183885280 hasConcept C180940675 @default.
- W3183885280 hasConcept C182037307 @default.
- W3183885280 hasConcept C193536780 @default.
- W3183885280 hasConcept C31972630 @default.
- W3183885280 hasConcept C41008148 @default.
- W3183885280 hasConcept C4199805 @default.
- W3183885280 hasConcept C47432892 @default.
- W3183885280 hasConcept C76155785 @default.
- W3183885280 hasConcept C9417928 @default.
- W3183885280 hasConcept C94915269 @default.
- W3183885280 hasConcept C99498987 @default.