Efficient Predictive Algorithms for Image Compression -

Lu?s Filipe Ros?rio Lucas was born in Portugal in 1988. He received the Engineering and M.Sc. degrees in Electrical Engineering from Escola Superior de Tecnologia e Gest?o of Instituto Polit?cnico de Leiria, Portugal, in 2009 and 2011, respectively, and the Ph.D. degree from the Universidade Federal do Rio de Janeiro, Brazil, in 2016, in collaboration with the Instituto de Telecomunica??es, Portugal. Currently, he is a researcher at the Instituto de Telecomunica??es, in Leiria, Portugal. His research interests include image and video compression, digital signal processing and embedded systems.

Eduardo Ant?nio Barros da Silva was born in Rio de Janeiro, Brazil, in 1963. He got his B.Sc in Engineering from Instituto Militar de Engenharia (IME) in 1984, his M.Sc in Electrical Engineer from COPPE/UFRJ in 1990 and his Ph.D. in Electronics Systems Engineering from Essex University, England in 1995. Since 1989 he works at the Electronics and Computer Science Departament from Escola Polit?cnica (former Escola de Engenharia), from Universidade Federal do Rio de Janeiro (UFRJ). He was coordinator of the specialization course in Telecommunication Systems from Escola Polit?cnica (TELECOM) from 2003 to 2008. He also works since 1996 at the Programa de Engenharia El?trica from COPPE/UFRJ, where he was Head of Department in 2002. He gives consulting and training in Image and Video Compression for TV operators in Brazil. In 1994 he won the British Telecom Postgraduate Publication Prize for his IEEE article on Aliasing in Subband Coding. He has been appointed a Distinguished Lecturer of the IEEE CAS Society for 2003 and 2004. His research interesses are in the areas of Digital Signal and Image Processing, Signal Coding, Digital Television, Wavelet Transforms, Mathematical Morphology and Telecommunications Applications. He is a member of IEEE, of the Brazilian Telecommunication Society (SBrT) and the Brazilian Television Engineering Society (SET).

S?rgio Manuel Maciel de Faria was born in Portugal in 1965. He received the Engineering degree in Electrical Engineering from Universidade de Coimbra, Portugal, in 1988, the M.Sc. degree in Electrical Engineering from Universidade de Coimbra, Portugal, in 1992, and the Ph.D. degree in Electronics and Telecommunications from the University of Essex, England, in 1996. In 2014 received the title of Agregado by Instituto Superior T?cnico, University of Lisbon. He is Professor with the Department of Electrical Engineering, in Escola Superior de Tecnologia e Gest?o of Instituto Polit?cnico de Leiria, Portugal, since 1990. He is an Auditor with A3ES organization for Electrical and Electronic Engineering courses in Portugal. He is a Senior Researcher with Instituto de Telecomunica??es. His research interests include 2D/3D image and video processing and coding, motion representation, and medical imaging. He is an Area Editor of Signal Processing: Image Communication. He has been a Scientific and Program Committee Member of many international conferences. He is a reviewer for several international scientific journals and conferences (IEEE, IET and EURASIP). He is a Senior Member of the IEEE.

Nuno Miguel Morais Rodrigues graduated in electrical engineering in 1997, received the M.Sc. degree from the Universidade de Coimbra, Coimbra, Portugal, in 2000, and the Ph.D. degree from the Universidade de Coimbra, in 2009, in collaboration with the Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.

Since 1997, he has been with the Department of Electrical Engineering, Escola Superior de Tecnologia e Gest?o, Instituto Polit?cnico de Leiria, Leiria, Portugal. Since 1998, he has been with the Instituto de Telecomunica??es, Portugal, ...

Sommaire:
1 Introduction1.1 Motivation1.2 Objectives and contributions of the book1.3 Outline of the book2 Prediction techniques for image and video coding2.1 Digital video representation2.2 Image prediction overview2.3 State-of-the-art prediction methods2.3.1 Intra-frame prediction2.3.2 Inter-frame prediction2.4 Least-squares prediction methods2.4.1 Linear prediction of images and video using LSP2.4.2 Context-based adaptive LSP2.4.3 Block-based LSP2.4.4 Spatio-temporal LSP2.5 Sparse representation for image prediction2.5.1 Sparse prediction problem formulation2.5.2 Matching Pursuit methods2.5.3 Template Matching algorithm2.5.4 Neighbour embedding methods2.6 Conclusions3 Image and video coding standards3.1 Hybrid video compression3.2 Compression of 2D video3.2.1 H.265/HEVC standard3.2.2 Experimental results3.3 Compression of 3D video3.3.1 3D video systems3.3.2 3D video coding standards3.3.3 Experimental results3.4 Conclusions4 Compression of depth maps using predictive coding4.1 Overview of intra techniques for depth map coding4.1.1 Directional intra prediction4.1.2 Depth Modelling Modes4.1.3 Depth Lookup Table4.1.4 Segment-wise DC Coding4.1.5 Single Depth Intra Mode4.1.6 View Synthesis Optimisation4.2 Overview of Predictive Depth Coding4.3 Coding techniques of PDC algorithm4.3.1 Flexible block partitioning4.3.2 Directional intra prediction framework4.3.3 Constrained Depth Modelling Mode4.3.4 Residual signal coding4.3.5 Bitstream syntax and context modelling4.4 PDC encoder control4.5 Experimental Results4.5.1 Evaluation of PDC algorithm for intra coding4.5.2 Evaluation of PDC algorithm using VSO metric4.5.3 Evaluation of PDC algorithm combined with 3D-HEVC standard4.6 Conclusions5 Sparse representation methods for image prediction5.1 3D holoscopic image coding using LLE-based prediction5.1.1 Proposed HEVC encoder using LLE-based prediction5.1.2 Experimental Results5.2 The sparse-LSP method for intra prediction5.2.1 Algorithm description5.2.2 Mathematical interpretation5.3 Application of sparse-LSP to HEVC standard5.3.1 Implementation details5.3.2 Experimental results5.4 Conclusions6 Generalised optimal sparse predictors6.1 Two-stage interpretation of directional prediction6.2 Generalising directional prediction6.3 Sparse model estimation algorithms6.3.1 Matching Pursuit algorithms6.3.2 Least Angle Regression6.3.3 LASSO regression6.3.4 Elastic Net regression6.4 Proposed algorithm based on adaptive sparse predictors for HEVC6.5 Experimental results6.5.1 Effect of sparsity constraints6.5.2 Regularisation parameters for optimal RD performance6.5.3 RD performance relative to other intra prediction methods6.6 Conclusions7 Conclusions and other research directions8 Test signals8.1 Test images8.2 Holoscopic imagesReferences