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Menon, Daniele (2009) Color Image Reconstruction for Digital Cameras. [Tesi di dottorato]

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Abstract (inglese)

Recently we observed a fast diffusion of digital cameras that are able to acquire images and videos directly in the digital format. This new acquisition technique allowed to explore new strategies to process, save and display images and videos.

Digital cameras require many operations to process the data acquired by the sensor. In this thesis I present an overview of the techniques used in practical realizations and proposed in the literature. Particular attention is paid to the algorithms that are more connected to the image processing area.

Among them, the process that is the most important for the quality of the resulting images and the most computational demanding is demosaicking. This consists in the reconstruction of the full color representation of an image from the data acquired by a sensor provided with a color filter array that in each pixel acquires a color component only instead of the three values that are necessary to represent a color image. The most common color filter array is called Bayer pattern, from the name of his inventor Bryce Bayer. In this thesis an overview of the demosaicking techniques presented in the literature is given and three new methods that allow to obtain good performances with a reduced computational cost are proposed. The first two are based on directional interpolations and are made adaptive to the image behavior through analysis of the edges and wavelet transformations. The last proposed technique, instead, is based on regularization methods, an useful tool to find a solution for an ill-conditioned inverse problem.

Since the sensor introduces a noisy component in the acquired data, an algorithm to perform demosaicking and denoising jointly is also analyzed. It exploits wavelet transformations.

Finally, a method to adaptively interpolate the image is presented, in order to increase the resolution and improve the visual quality of the details in the image. This technique is based on an analysis of the statistical local behavior of the image.

Abstract (italiano)

Negli ultimi anni abbiamo assistito ad una rapida diffusione di fotocamere e telecamere in grado di acquisire immagini e video direttamente in formato digitale. Questo nuovo tipo di acquisizione ha dato la possibilità di esplorare nuove strategie per l'elaborazione, l'archiviazione e la visualizzazione delle immagini e dei video.

Le fotocamere (e telecamere) digitali richiedono un elevato numero di operazioni per elaborare i dati acquisiti dal sensore. In questa tesi viene offerta una panoramica delle tecniche utilizzate nella pratica e di quelle presentate nella letteratura scientifica. In particolare, si è data particolare attenzione agli algoritmi maggiormente legati all'area dell'elaborazione dei segnali.

Tra questi, il procedimento più importante per la qualità finale dell'immagine e più impegnativo per le risorse computazionali delle fotocamere è senza dubbio il demosaicking (traducibile con demosaicizzazione). Esso consiste nella ricostruzione della rappresentazione a colori dell'immagine a partire dai dati acquisiti con un color filter array che, in ogni pixel, preleva una sola componente di colore invece delle tre necessarie per la visualizzazione di un'immagine a colori. Un color filter array molto diffuso è il Bayer pattern, così chiamato dal nome del suo inventore Bryce Bayer. All'interno della tesi viene fornita un'ampia panoramica delle strategie proposte per il demosaicking nella letteratura scientifica e, inoltre, vengono presentati tre nuovi approcci in grado di fornire ottime prestazioni nonostante il loro ridotto costo computazionale. I primi due sono basati su interpolazioni direzionali e resi adattivi al contenuto dell'immagine attraverso opportune analisi del comportamento dei bordi e delle trasformazioni wavelet. Un'altra tecnica proposta, invece, è basata sui metodi di regolarizzazione, utili per trovare soluzioni in problemi matematicamente non invertibili.

Dal momento che i sensori aggiungono una componente rumorosa ai dati acquisiti, viene analizzato anche un algoritmo che permette di effettuare congiuntamente demosaicking e denoising utilizzando delle trasformazioni wavelet.

In conclusione, viene presentato un metodo per effettuare un'interpolazione adattiva dei dati in modo da aumentare la risoluzione e migliorare la visione dei dettagli. Tale tecnica si basa su un'analisi del comportamento statistico locale dell'immagine.

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Tipo di EPrint:Tesi di dottorato
Relatore:Calvagno, Giancarlo
Dottorato (corsi e scuole):Ciclo 21 > Scuole per il 21simo ciclo > INGEGNERIA DELL'INFORMAZIONE > INGEGNERIA ELETTRONICA E DELLE TELECOMUNICAZIONI
Data di deposito della tesi:28 Gennaio 2009
Anno di Pubblicazione:28 Gennaio 2009
Parole chiave (italiano / inglese):image processing, interpolation, demosaicking, demosaicing, digital camera
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/03 Telecomunicazioni
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Codice ID:1577
Depositato il:28 Gen 2009
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