Pregled bibliografske jedinice broj: 306069
ROBUST BLIND SEPARATION OF STATISTICALLY DEPENDENT SOURCES USING DUAL TREE WAVELETS
ROBUST BLIND SEPARATION OF STATISTICALLY DEPENDENT SOURCES USING DUAL TREE WAVELETS // 2007 IEEE Conference on Image Processing
San Antonio (TX), Sjedinjene Američke Države: Institute of Electrical and Electronics Engineers (IEEE), 2007. str. I-433 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 306069 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
ROBUST BLIND SEPARATION OF STATISTICALLY DEPENDENT SOURCES USING DUAL TREE WAVELETS
Autori
Kopriva, Ivica ; Seršić, Damir ;
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2007 IEEE Conference on Image Processing
/ - : Institute of Electrical and Electronics Engineers (IEEE), 2007, I-433
ISBN
1-4244-1437-7
Skup
2007 IEEE Conference on Image Processing
Mjesto i datum
San Antonio (TX), Sjedinjene Američke Države, 16.09.2007. - 19.09.2007
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
blind source separation; statistically dependent sources; dual tree wavelets; independent component analysis; mutual information
Sažetak
Blind source separation (BSS) problem is commonly solved by means of independent component analysis (ICA)assuming statistically independent and non-Gaussian sources. The strict independence assumption can be relaxed to existence of subbands where signals are less dependent. In this paper, we use dual tree complex wavelets for the subband decomposition of observed signals and small cummulant based approximation of mutual information for finding the most independent subband(s). We compare the proposed method to previously reported shift invariant and decimated wavelet packet based approach, as well as to innovations based approach. We found proposed dual tree wavelets scheme as an efficient and robust solution of the BSS problem of statistically dependent sources. One important application of the proposed method is related to unsupervised segmentation of medical and remotely sensed multispectral images.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
036-0362214-1989 - Inteligentne metode obrade i analize slika (Lončarić, Sven, MZO ) ( CroRIS)
098-0982903-2558 - Analiza višespektralih podataka (Kopriva, Ivica, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Institut "Ruđer Bošković", Zagreb
