Matches in UGent Biblio for { <https://biblio.ugent.be/publication/1053617#aggregation> ?p ?o. }
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- aggregation classification "P1".
- aggregation creator B71501.
- aggregation creator person.
- aggregation date "2009".
- aggregation hasFormat 1053617.bibtex.
- aggregation hasFormat 1053617.csv.
- aggregation hasFormat 1053617.dc.
- aggregation hasFormat 1053617.didl.
- aggregation hasFormat 1053617.doc.
- aggregation hasFormat 1053617.json.
- aggregation hasFormat 1053617.mets.
- aggregation hasFormat 1053617.mods.
- aggregation hasFormat 1053617.rdf.
- aggregation hasFormat 1053617.ris.
- aggregation hasFormat 1053617.txt.
- aggregation hasFormat 1053617.xls.
- aggregation hasFormat 1053617.yaml.
- aggregation isPartOf urn:isbn:9781424423538.
- aggregation isPartOf urn:issn:1520-6149.
- aggregation language "eng".
- aggregation publisher "IEEE".
- aggregation subject "Technology and Engineering".
- aggregation title "Gray-scale erosion algorithm based on image bitwise decomposition: application to focal plane processors".
- aggregation abstract "A novel approach to implement gray-scale morphological operations is presented in this work. This new technique is based on the bitwise decomposition of the gray-scale image, yielding bitplanes disposed according to their bit of significance. It is of particular interest for implementations on Focal Plane Processors. Our approach relies on the binary search method to obtain either the maximum or minimum on a local neighborhood by manipulating the binary levels resulting from the bitwise decomposition with simple logic functions. This contrasts significantly with the classical Threshold Decomposition (TD) approach, on which most of the current techniques are based on. Our method shows better efficiency than TD implementations. Further gains can be obtained because our method shows a strong dependency on the image dynamic range.".
- aggregation authorList BK182096.
- aggregation endPage "848".
- aggregation startPage "845".
- aggregation isDescribedBy 1053617.
- aggregation similarTo ICASSP.2009.4959716.
- aggregation similarTo LU-1053617.