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Nonlinear techniques of noise reduction in digital color images

Autorzy
Smołka B.
Identyfikatory
Warianty tytułu
PL
Nieliniowe techniki redukcji szumu w barwnych obrazach cyfrowych
Języki publikacji
EN
Abstrakty
EN
This monograph details the author's most important contributions to the rapidly growing field of nonlinear noise reduction in color images. Its content is structured into seven Chapters. The first Chapter describes the fundamentals of color image processing and also presents the sources of image noise, describes their models and defines measures of the quality of image restoration. The second Chapter is focused on the nonlinear adaptive schemes of noise reduction applied in gray scale imaging, which are very often extendable into the multichannel case. Chapter 3 provides the state of the art in color image filtering and serves as a basis for the remaining Chapters, in which author's original contributions are presented. In the next Chapter, the robust anisotropic diffusion filtering scheme, which ignores the central pixel of the filtering window, when building the weighted average of the input samples is introduced. This improvement allows to use the anisotropic technique for the suppression of strong Gaussian and heavy tailed noise, as the influence of the central, corrupted pixel is diminished by an appropriate setting of the conductivity coefficients. In this Chapter the iterative forward and backward diffusion technique is also presented. Chapter 5 is devoted to the development of a powerful class of filters, based on the digital paths concepts and fuzzy similarity measures among pixels in neighborhood relation. This novel technique, which utilizes the connection between image pixels, instead of window based structures, is an extension of the adaptive noise reduction filtering and anisotropic diffusion techniques and is shown to have advantages over traditional methods. The extensive simulations reveal that the proposed filtering framework significantly excels over the standard methods and can be applied for the removal of both Gaussian and impulsive noise. In the next Chapter the problem of nonparametric impulsive noise reduction in multichannel images is addressed. A new family of filters for noise attenuation elaborated by the author, based on the nonparametric probability density estimation of the sample data, is introduced and its relationship to commonly used filtering techniques is investigated. The last Chapter deals with the adaptive optimization of the weighted vector median filters and also introduces the new technique based on the so called sigma-filtering. This novel adaptive technique is based on robust order statistic concepts and simplified statistical measures of vectors' dispersion.
PL
Redukcja szumów jest jednym z najważniejszych etapów przetwarzania wstępnego obrazów cyfrowych. Efektywna filtracja sygnału wizyjnego warunkuje bowiem sukces dalszych etapów jego przetwarzania. Problem redukcji szumów jest szczególnie trudny w przypadku obrazów barwnych, albowiem nie została jak dotąd stworzona spójna teoria umożliwiająca bezpośrednią implementację dobrze poznanych filtrów eliminacji szumów w obrazach z poziomami szarości do poprawy jakości obrazów wielokanałowych. W ciągu ostatnich lat zaproponowano liczne algorytmy redukcji szumów w obrazach barwnych. Najprostszą klasą są filtry liniowe, które mogą efektywnie usuwać addytywne szumy gaussowskie, jednakże nie są one zdolne do adaptacji do nieliniowości występujących w obrazie, co prowadzi do rozmywania krawędzi obiektów oraz innych, ważnych z punktu widzenia percepcji człowieka oraz dalszych etapów przetwarzania, struktur obrazu. Aby poprawić efektywność filtracji szumów, na przestrzeni ostatnich lat zaproponowano różnorodne techniki nieliniowe, z których najpopularniejszą grupę stanowią filtry bazujące na statystykach porządkowych. Filtry rangowe, minimalizujące skumulowaną funkcję dystansową, są skuteczne w usuwaniu szumów impulsowych, jednakże ich wadą jest zbyt duża inwazyjność, manifestująca się w zastępowaniu nie tylko pikseli obrazu, które uległy kontaminacji, ale także pikseli oryginalnych, co prowadzi do destrukcji drobnych struktur obrazu o wielkości porównywalnej z wymiarami okna filtracyjnego. Dodatkową wadą tych filtrów jest ich nieskuteczność w redukcji szumu gaussowskiego. Niniejsza monografia stanowi podsumowanie wysiłku badawczego autora w dziedzinie filtracji szumów występujących w barwnych obrazach cyfrowych. W pracy przedstawiono różnorodne klasy filtrów zaprojektowanych do eliminacji zakłóceń impulsowych, szumów gaussowskich oraz najbardziej degradujących obraz szumów mieszanych. Przedstawione w monografii algorytmy cechują się bardzo dobrą efektywnością, przewyższającą znacznie algorytmy standardowe, oraz niską złożonością obliczeniową, umożliwiającą ich zastosowanie w realizacjach praktycznych, szczególnie w systemach wizyjnych czasu rzeczywistego. Rozdział pierwszy monografii stanowi wprowadzenie do problematyki przetwarzania barwnych obrazów cyfrowych. W rozdziale tym przedstawiono podstawowe koncepcje tworzenia wielokanałowego obrazu cyfrowego i jego filtracji, koncentrując się na problemie zakłóceń obrazu powstających w procesie jego akwizycji, przetwarzania, transmisji oraz przechowywania na nośnikach danych. W rozdziale tym wprowadzono modele szumów symulujących rzeczywiste zakłócenia oraz przedstawiono metody oceny jakości obrazów cyfrowych umożliwiające ewaluację efektywności różnorodnych metod redukcji artefaktów wywołanych przez zjawiska szumu. W rozdziale drugim przedstawiono przegląd adaptacyjnych technik redukcji szumów gaussowskich, impulsowych oraz mieszanych w obrazach z poziomami szarości. W rozdziale tym omówiono algorytmy oparte na koncepcji nieliniowej średniej ważonej oraz dokonano przeglądu metod bazujących na statystykach porządkowych. Szczególną uwagę poświęcono ważonej medianie oraz iteracyjnym algorytmom wyznaczania optymalnych współczynników wagowych ze względu na zastosowanie tych metod do optymalizacji filtrów wektorowych przedstawionych w rozdziale siódmym. Rozdział trzeci poświęcony jest omówieniu metod redukcji szumów występujących w barwnych obrazach cyfrowych. Szczegółowo opisano filtry oparte na statystykach porządkowych, transformacjach wykorzystujących koncepcje teorii zbiorów rozmytych, a także metody wykorzystujące estymację nieparametryczną. Szczególną uwagę poświęcono ważonej medianie wektorowej oraz zaproponowanej przez autora jej modyfikacji, prowadzącej do przyśpieszenia algorytmu oraz poprawy efektywności procesu filtracji. Rozdział czwarty, nawiązujący do rozdziału drugiego, poświęcony jest dyfuzji anizotropowej, stanowiącej skuteczną metodę redukcji szumów gaussowskich. W rozdziale tym przedstawione zostały wyniki prac autora nad modyfikacją algorytmu dyfuzji anizotropowej, poprzez minimalizację wpływu centralnego piksela maski filtracyjnej, umożliwiającą także redukcję szumów impulsowych. W rozdziale tym opisano ponadto opracowaną przez autora metodę iteracyjną, opartą na technice nieostrego maskowania, wykorzystującą tak zwaną dyfuzję odwrotną do poprawy jakości obrazów, które uległy kontaminacji szumem gaussowskim. Koncepcja minimalizacji wpływu centralnego piksela w masce filtracyjnej została rozwinięta w rozdziale piątym, w którym przedstawiono wyniki prac autora nad nową klasą filtrów opartych na ścieżkach cyfrowych i elementach teorii zbiorów rozmytych. Algorytmy redukcji szumów, wykorzystujące ideę eksploracji otoczenia centralnego piksela maski filtracyjnej przez ścieżki cyfrowe wyznaczające poprzez funkcję kosztu optymalne połączenia pikseli obrazu, cechują się świetną efektywnością redukcji szumów impulsowych, gaussowskich i mieszanych. Opracowane przez autora metody stanowią uogólnienie i rozwinięcie dyfuzji anizotropowej przedstawionej w rozdziale czwartym i stanowią jego najbardziej znaczący wkład w rozwój nieliniowych metod redukcji szumów w barwnych obrazach cyfrowych. Rozdział szósty poświęcony jest zastosowaniu estymacji nieparametrycznej do filtracji szumów impulsowych. W rozdziale tym przedstawiono ogólną koncepcję filtrów opartych na estymacie nieparametrycznej, wskazując na ich podobieństwo do mediany wektorowej, w przypadku gdy funkcja jądra ma postać funkcji liniowej. W rozdziale tym wprowadzono także rodzinę filtrów cechującą się dużą skutecznością w redukcji szumów impulsowych oraz zdolnością do zachowywania krawędzi obrazu i jego tekstury. Własności te osiągane są przez zaimplementowane mechanizmy adaptacyjne, dostosowujące parametry filtrów do struktur morfologicznych obrazu oraz poziomu jego zakłóceń. Na uwagę zasługuje mała złożoność obliczeniowa przedstawionych klas filtrów, pozwalająca na ich zastosowanie do przetwarzania obrazów w czasie rzeczywistym. W rozdziale siódmym przedstawiono nowe metody optymalizacji ważonej mediany wektorowej za pomocą optymalizacji liniowej oraz sigmoidalnej, omówionej w rozdziale drugim. Przedstawione metody optymalizacji, operujące zarówno na chrominancji, jak i na luminancji obrazu, prowadzą do wyznaczania optymalnych z punktu widzenia zadanej funkcji kosztu współczynników wektora wag. W rozdziale tym wprowadzono także adaptacyjną metodę eliminacji szumów impulsowych opartą na estymacji dyspersji elementów obrazu zawartych w oknie filtracyjnym. Ta nowa klasa filtrów, bazująca na koncepcji filtru typu sigma, charakteryzuje się dużą efektywnością redukcji szumów impulsowych oraz niską złożonością obliczeniową.
Słowa kluczowe
EN
PL
Wydawca
Wydawnictwo Politechniki Śląskiej
Czasopismo
Zeszyty Naukowe. Automatyka / Politechnika Śląska
Rocznik
2004
Tom
z. 139
Strony
7--212
Opis fizyczny
Bibliogr. 430 poz.
Twórcy
autor
Smołka B.
  • Instytut Automatyki Politechniki Śląskiej, 44-100 Gliwice, ul. Akademicka 16, tel. (032) 237-19-12, bogdan.smolka.@polsl.pl
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