Luong, Huynh Van

I dag kræver nye applikationer, såsom trådløse visuelle sensornetværk og trådløs videoovervågning, simpel videoindkodning med høj kodningseffektivitet og robusthed overfor fejl. Distributed Video Coding (DVC) er et nyt kodningsparadigme, som udnytter kildestatistikken ved dekoderen og kan dermed være en fordel ved førnævnte applikationer. Selvom der er blevet udviklet avancerede teknikker til forbedring af DVC, er forbedring af DVC kodning stadig udfordrende.Denne afhandling tager denne udfordring op ved at foreslå flere iterative algoritmer på forskellige niveauer, f.eks. på bitplane-, band-, og frame-niveau. For at vise det teoretiske grundlag bliver teorien for DVC introduceret. Den første foreslåede algoritme benytter parallel iterativ afkodning ved hjælp af flere LDPC dekodere for at udnytte korrelationen bitplaner imellem. For at forbedre estimeringen af sideinformationen (SI), støjmodelleringen og samtidig lære af de tidligere dekodede Wyner-Ziv (WZ) frames, foreslås ”Side Information and Noise learninG”(SING). SING introducerer optisk flow for at kompensere for de svagheder i blokken, der skyldes SI-estimeringen og udnytter også grupperingen af DCT-blokkene for at fange korrelationen forskellige bands imellem, samtidig med at øge den lokale tilpasning i støjmodellering. Under afkodning bliver de opdaterede oplysninger anvendt til iterativt at opdatere den beregnede bevægelse og gendannelse i den foreslåede ”MOtion and REconstruction reestimation”(MORE) metode. MORE opdaterer ikke kun bevægelsesvektorerne for at forbedre SI og støj-modelleringen, men kompenserer også residualet af bevægelsen baseret på de tidligere dekodede WZ frames. Endvidere øger MORE gendannelsen ved at foreslå en generaliseret rekonstruktion ved at optimere rekonstruktionen med flere konkurrencedygtige SI’er. Endelig foreslås en adaptiv algoritme til tilstandsbeslutning som drager fordel af skip og intratilstandene i DVC. Dette sker på basis af kvaliteten i nøgle frames og raten for WZ frames. Samlet set forbedrer de foreslåede algoritmer i en væsentlig grad kodningseffektiviteten af DVC og bidrager med værdifulde løsninger for nye videoapplikationer.Nowadays, emerging applications such as wireless visual sensor networks and wireless video surveillance are requiring lightweight video encoding with high coding efficiency and error-resilience. Distributed Video Coding (DVC) is a new coding paradigm which exploits the source statistics at the decoder side offering such benefits for these applications. Although there have been some advanced improvement techniques, improving the DVC coding efficiency is still challenging.The thesis addresses this challenge by proposing several iterative algorithms at different working levels, e.g. bitplane, band, and frame levels. In order to show the information theoretic basis, theoretical foundations of DVC are introduced. The first proposed algorithm applies parallel iterative decoding using multiple LDPC decoders to utilize cross bitplane correlation. To improve Side Information (SI) generation and noise modeling and also learn from the previous decoded Wyner-Ziv (WZ) frames, side information and noise learning (SING) is proposed. The SING scheme introduces an optical flow technique to compensate the weaknesses of the block based SI generation and also utilizes clustering of DCT blocks to capture cross band correlation and increase local adaptivity in noise modeling. During decoding, the updated information is used to iteratively reestimate the motion and reconstruction in the proposed motion and reconstruction reestimation (MORE) scheme. The MORE scheme not only reestimates the motion vectors for improving SI and noise modeling but also compensates the residual motion based on the previously decoded WZ frames. Furthermore, the MORE codec enhances the reconstruction by proposing a generalized reconstruction algorithm to optimize reconstructing with multiple competitive SIs. Finally, an adaptive mode decision is investigated to take advantage of skip and intra mode in DVC by deciding the coding modes based on the quality of key frames and rate of WZ frames. Overall, the proposed algorithms significantly improve the coding efficiency of DVC contributing valuable solutions for the emerging applications

Online Research Database In Technology

Distributed Video Coding: Iterative Improvements

http://orbit.dtu.dk/ws/files/56195668/a_Phd_thesis_print_version_huynh.pdf

Distributed Video Coding: Iterative Improvements

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Online Research Database In Technology