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Pregled bibliografske jedinice broj: 153282

Adaptation in the Quincunx Wavelet Filter Bank with Applications in Image Denoising


Vrankić, Miroslav; Seršić, Damir
Adaptation in the Quincunx Wavelet Filter Bank with Applications in Image Denoising // Proceedings of the 2004 International TICSP Workshop on Spectral Methods and Multirate Signal Processing, SMMSP 2004 / Astola, Jaako ; Egiazarian, Karen ; Saramaki, Tapio (ur.).
Tampere, Finska: Tampere International Center for Signal Processing, 2004. str. 245-252 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Adaptation in the Quincunx Wavelet Filter Bank with Applications in Image Denoising

Autori
Vrankić, Miroslav ; Seršić, Damir

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 2004 International TICSP Workshop on Spectral Methods and Multirate Signal Processing, SMMSP 2004 / Astola, Jaako ; Egiazarian, Karen ; Saramaki, Tapio - Tampere, Finska : Tampere International Center for Signal Processing, 2004, 245-252

Skup
2004 International TICSP Workshop on Spectral Methods and Multirate Signal Processing, SMMSP 2004

Mjesto i datum
Beč, Austrija, 11-12.09.2004

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Image denoising; wavelets; lifting scheme; adaptive filters

Sažetak
In this paper, we present the realization of an adaptive shift invariant wavelet transform defined on the quincunx grid. The wavelet transform relies on the lifting scheme which enables us to easily introduce the adaptation by splitting the predict stage into two parts. The first part of the predict stage is fixed and guarantees the number of vanishing moments of the wavelet filter bank while the second part can adapt to the local properties of the analyzed image. In this paper, we explore the robustness of the generalized least squares adaptation algorithm to the noise present in the analyzed image. The denoising results obtained with the nonseparable adaptive wavelet transform have been compared with results obtained with both separable and nonseparable fixed wavelet transforms. Also, the empirical Wiener filtering in the wavelet domain has been used in order to further improve the denoising results.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekt / tema
0036028
0036029
0036054

Ustanove
Fakultet elektrotehnike i računarstva, Zagreb