IEEE Trans Image Process - Lazy sliding window implementation of the bilateral filter on parallel architectures.

Tópicos

{ imag(2830) propos(1344) filter(1198) }
{ algorithm(1844) comput(1787) effici(935) }
{ perform(1367) use(1326) method(1137) }
{ concept(1167) ontolog(924) domain(897) }
{ control(1307) perform(991) simul(935) }
{ decis(3086) make(1611) patient(1517) }
{ imag(2675) segment(2577) method(1081) }
{ method(984) reconstruct(947) comput(926) }
{ system(1976) rule(880) can(841) }
{ take(945) account(800) differ(722) }
{ motion(1329) object(1292) video(1091) }
{ research(1085) discuss(1038) issu(1018) }
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{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
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{ can(774) often(719) complex(702) }
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{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
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{ bind(1733) structur(1185) ligand(1036) }
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{ featur(3375) classif(2383) classifi(1994) }
{ network(2748) neural(1063) input(814) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
{ assess(1506) score(1403) qualiti(1306) }
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{ state(1844) use(1261) util(961) }
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{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
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{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
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{ can(981) present(881) function(850) }
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{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
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{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Bilateral filter is one of the state-of-the-art methods for noise reduction in images. The plausible visual result the filter produces makes it a common choice for image and video processing applications, yet, its high computational complexity makes a real-time implementation a challenging task. Presented here is a parallel version of the bilateral filter using a lazy sliding window, suitable for SIMD-type architectures.

Resumo Limpo

bilater filter one stateoftheart method nois reduct imag plausibl visual result filter produc make common choic imag video process applic yet high comput complex make realtim implement challeng task present parallel version bilater filter use lazi slide window suitabl simdtyp architectur

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