Adaptive lifting scheme for nonseparable two-dimensional wavelet transforms

doctoral thesis

• Title (croatian): Adaptivna shema podizanja za neseparabilne dvodimenzionalne valićne transformacije
• Author: Miroslav Vrankić
• Mentor: Damir Seršić (mentor)
• Committee member: Sven Lončarić (predsjednik povjerenstva)
• Committee member: Damir Seršić (član povjerenstva)
• Committee member: Hrvoje Šikić (član povjerenstva)
• Committee member: Sonja Grgić (član povjerenstva)
• Committee member: Atanas Gotchev (član povjerenstva); VIAF: 305044237
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; (Department of Electronic Systems and Information Processing); Zagreb
• Defense date and country: 2006-07-06, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering; Electronics
• Universal decimal classification (UDC): 621.3 - Electrical engineering

Abstract

In this thesis, we propose the novel adaptive wavelet filter bank structures that are used to obtain efficient representations of the analyzed images. We present the lifting scheme structures for building adaptive wavelet decompositions based on the nonseparable quincunx sampling scheme. The resulting wavelet decompositions are adaptive to the local properties of the analyzed image. Despite the introduced adaptation, a desired number of vanishing moments is still retained. The proposed adaptation is performed in order to minimize the energy of detail coefficients on a neighborhood of each pixel of the analyzed image. The appropriate neighborhood is determined for each pixel separately by using the intersection of confidence intervals (ICI) rule. The application of the ICI rule improves the estimation of the filter bank parameters and makes it more robust to noise. The image denoising results are presented for both synthetic and real-world images. It is shown that the adaptive wavelet decompositions outperform the existing fixed decompositions in terms of denoising quality of images that contain periodic components, and in general they give more compact image representations.

Abstract (croatian)

U ovoj disertaciji predlažemo nove adaptivne valićne filtarske strukture koje se koriste za dobivanje efikasnih reprezentacija analiziranih slika. U radu prikazujemo filtarske slogove temeljene na shemi podizanja za konstrukciju adaptivnih valićnih razlaganja zasnovanih na neseparabilnom quincunx uzorkovanju. Rezultirajuća valićna razlaganja su prilagođena lokalnim svojstvima analizirane slike. Unatoč uvedenoj adaptaciji, zadržan je željeni broj nul-momenata pripadajućihih vali ćnih funkcija. Adaptacija se vrši sa ciljem minimizacije koeficijenata detalja na okolini svakog slikovnog elementa. Odabir odgovarajuće okoline za svaki slikovni element vrši se korištenjem metode presjecišta invervala pouzdanosti. Primjena dotične metode poboljšava adaptaciju parametara filtarskog sloga i čini je robusnijom na šum. Rezultati uklanjanja šuma iz slike prikazani su za primjere sintetičkih kao i realnih slika. Pokazano je da dobivena adaptivna valićna razlaganja nadmašuju postojeća fiksna razlaganja s obzirom na kvalitetu uklanjanja šuma iz slika koje sadrže periodičke komponente, te općenito daju kompaktniji zapis slike.

• Keywords: wavelet transforms; adaptive filters; second generation wavelets; adaptive lifting scheme; quincunx sampling; interpolating filters; intersection of confidence intervals; image denoising
• Keywords (croatian): valićne transformacije; adaptivni filtri; valići druge generacije; adaptivna shema podizanja; quincunx uzorkovanje; interpolacijski filtri; presjecište intervala pouzdanosti; uklanjanje šuma iz slike
• Language: english
• URN:NBN: urn:nbn:hr:168:544047
• Study programme: Title: Doctoral study programme "Electrical Engineering and Computing"; Study programme type: university; Study level: postgraduate; Academic / professional title: doktor/doktorica znanosti, po-dručje tehničkih znanosti (doktor/doktorica znanosti, po-dručje tehničkih znanosti)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-06-28 09:03:59