Design and Optimization of Graph Transform for Image and Video Compression

Tipo di pubblicazione: Tesi di dottorato
Tipologia MIUR: Tesi di dottorato > Tesi di dottorato - Polito
Titolo: Design and Optimization of Graph Transform for Image and Video Compression
Autori: Fracastoro, Giulia
Autori di ateneo:
Tutor: Magli E.
Dottorato di ricerca: I Ciclo > INGEGNERIA ELETTRONICA
Istituzione: Politecnico di Torino
Numero di pagine: 121
Abstract: The main contribution of this thesis is the introduction of new methods for designing adaptive transforms for image and video compression. Exploiting graph signal processing techniques, we develop new graph construction methods targeted for image and video compression applications. In this way, we obtain a graph that is, at the same time, a good representation of the image and easy to transmit to the decoder. To do so, we investigate different research directions. First, we propose a new method for graph construction that employs innovative edge metrics, quantization and edge prediction techniques. Then, we propose to use a graph learning approach and we introduce a new graph learning algorithm targeted for image compression that defines the connectivities between pixels by taking into consideration the coding of the image signal and the graph topology in rate-distortion term. Moreover, we also present a new superpixel-driven graph transform that uses clusters of superpixel as coding blocks and then computes the graph transform inside each region. In the second part of this work, we exploit graphs to design directional transforms. In fact, an efficient representation of the image directional information is extremely important in order to obtain high performance image and video coding. In this thesis, we present a new directional transform, called Steerable Discrete Cosine Transform (SDCT). This new transform can be obtained by steering the 2D-DCT basis in any chosen direction. Moreover, we can also use more complex steering patterns than a single pure rotation. In order to show the advantages of the SDCT, we present a few image and video compression methods based on this new directional transform. The obtained results show that the SDCT can be efficiently applied to image and video compression and it outperforms the classical DCT and other directional transforms. Along the same lines, we present also a new generalization of the DFT, called Steerable DFT (SDFT). Differently from the SDCT, the SDFT can be defined in one or two dimensions. The 1D-SDFT represents a rotation in the complex plane, instead the 2D-SDFT performs a rotation in the 2D Euclidean space.
Data: 2017
Status: Pubblicato
Lingua della pubblicazione: Inglese
Parole chiave:
Dipartimenti (originale): DET - Dipartimento di Elettronica e Telecomunicazioni
Dipartimenti: DET - Dipartimento di Elettronica e Telecomunicazioni
URL correlate:
    Area disciplinare: Area 09 - Ingegneria industriale e dell'informazione > TELECOMUNICAZIONI
    Data di deposito: 17 Mag 2017 10:54
    Data ultima modifica (IRIS): 17 Mag 2017 11:15:43
    Data inserimento (PORTO): 19 Mag 2017 04:23
    Numero Identificativo (DOI): 10.6092/polito/porto/2671060
    Permalink: http://porto.polito.it/id/eprint/2671060

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