000 03700nam a22005175i 4500
001 978-3-642-10695-8
003 DE-He213
005 20140220084529.0
007 cr nn 008mamaa
008 100301s2010 gw | s |||| 0|eng d
020 _a9783642106958
_9978-3-642-10695-8
024 7 _a10.1007/978-3-642-10695-8
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aBrox, Piedad.
_eauthor.
245 1 0 _aFuzzy Logic-Based Algorithms for Video De-Interlacing
_h[electronic resource] /
_cby Piedad Brox, Iluminada Baturone, Santiago Sánchez-Solano.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v246
505 0 _aBasic Concepts -- Fuzzy Motion-Adaptive Algorithm for Video De-Interlacing -- Design Options of the Fuzzy Motion-Adaptive Algorithm -- Fuzzy Motion-Adaptive De-Interlacing with Edge-Adaptive Spatial Interpolation -- Fuzzy Motion-Adaptive De-Interlacing with Smart Temporal Interpolation.
520 _aThe ‘Fuzzy Logic’ research group of the Microelectronics Institute of Seville is composed of researchers who have been doing research on fuzzy logic since the beginning of the 1990s. Mainly, this research has been focused on the microelectronic design of fuzzy logic-based systems using implementation techniques which range from ASICs to FPGAs and DSPs. Another active line was the development of a CAD environment, named Xfuzzy, to ease such design. Several versions of Xfuzzy have been and are being currently developed by the group. The addressed applications had basically belonged to the control field domain. In this sense, several problems without a linear control solution had been studied thoroughly. Some examples are the navigation control of an autonomous mobile robot and the level control of a dosage system. This book is organized in five chapters. In Chapter 1, some basic concepts are explained to completely understand the contribution of the algorithms developed in this research work. The evaluation of how motion is present and how it influences on de-interlacing is studied in Chapter 2. The design options of the proposed fuzzy motion-adaptive de-interlacing algorithm is studied in Chapter 3. A spatial interpolator that adapts the interpolation to the presence of edges in a fuzzy way is developed in Chapter 4. A temporal interpolator that adapts the strategy of the interpolation to possible repetition of areas of fields is presented in Chapter 5. Using both interpolators in the fuzzy motion-adaptive algorithm described in Chapter 3 clearly improves the de-interlaced results.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aComputer vision.
650 0 _aTelecommunication.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aCommunications Engineering, Networks.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aBaturone, Iluminada.
_eauthor.
700 1 _aSánchez-Solano, Santiago.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642106941
830 0 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v246
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-10695-8
912 _aZDB-2-ENG
999 _c111770
_d111770