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Efficient predictive algorithms for ...

Lucas, Luis Filipe Rosario.

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Efficient predictive algorithms for image compression

Record Type:	Electronic resources : Monograph/item
Title/Author:	Efficient predictive algorithms for image compression/ by Luis Filipe Rosario Lucas ... [et al.].
other author:	Lucas, Luis Filipe Rosario.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xix, 169 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction -- Prediction techniques for image and video coding -- Image and video coding standards -- Compression of depth maps using predictive coding -- Sparse representation methods for image prediction -- Generalised optimal sparse predictors -- Conclusions and other research directions -- Test signals -- References.
Contained By:	Springer eBooks
Subject:	Image compression. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-51180-1
ISBN:	9783319511801

Efficient predictive algorithms for image compression
Efficient predictive algorithms for image compression[electronic resource] /by Luis Filipe Rosario Lucas ... [et al.]. - Cham :Springer International Publishing :2017. - xix, 169 p. :ill. (some col.), digital ;24 cm.

Introduction -- Prediction techniques for image and video coding -- Image and video coding standards -- Compression of depth maps using predictive coding -- Sparse representation methods for image prediction -- Generalised optimal sparse predictors -- Conclusions and other research directions -- Test signals -- References.

This book discusses efficient prediction techniques for the current state-of-the-art High Efficiency Video Coding (HEVC) standard, focusing on the compression of a wide range of video signals, such as 3D video, Light Fields and natural images. The authors begin with a review of the state-of-the-art predictive coding methods and compression technologies for both 2D and 3D multimedia contents, which provides a good starting point for new researchers in the field of image and video compression. New prediction techniques that go beyond the standardized compression technologies are then presented and discussed. In the context of 3D video, the authors describe a new predictive algorithm for the compression of depth maps, which combines intra-directional prediction, with flexible block partitioning and linear residue fitting. New approaches are described for the compression of Light Field and still images, which enforce sparsity constraints on linear models. The Locally Linear Embedding-based prediction method is investigated for compression of Light Field images based on the HEVC technology. A new linear prediction method using sparse constraints is also described, enabling improved coding performance of the HEVC standard, particularly for images with complex textures based on repeated structures. Finally, the authors present a new, generalized intra-prediction framework for the HEVC standard, which unifies the directional prediction methods used in the current video compression standards, with linear prediction methods using sparse constraints. Experimental results for the compression of natural images are provided, demonstrating the advantage of the unified prediction framework over the traditional directional prediction modes used in HEVC standard. Presents a state-of-the-art review of existing prediction technologies for compression of both 2D and 3D multimedia content; Discusses the most recent advances beyond the current, standardized technologies for image and video compression, such as using the HEVC standard in the context of natural images, 3D and Light Field content; Includes new prediction methods based on alternative techniques and concepts, including flexible block partitioning, linear prediction, sparse representation.

ISBN: 9783319511801

Standard No.: 10.1007/978-3-319-51180-1doiSubjects--Topical Terms:

660231
Image compression.

LC Class. No.: TA1632

Dewey Class. No.: 005.746

Efficient predictive algorithms for image compression
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245 0 0 $a Efficient predictive algorithms for image compression $h [electronic resource] / $c by Luis Filipe Rosario Lucas ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xix, 169 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Introduction -- Prediction techniques for image and video coding -- Image and video coding standards -- Compression of depth maps using predictive coding -- Sparse representation methods for image prediction -- Generalised optimal sparse predictors -- Conclusions and other research directions -- Test signals -- References.
520 $a This book discusses efficient prediction techniques for the current state-of-the-art High Efficiency Video Coding (HEVC) standard, focusing on the compression of a wide range of video signals, such as 3D video, Light Fields and natural images. The authors begin with a review of the state-of-the-art predictive coding methods and compression technologies for both 2D and 3D multimedia contents, which provides a good starting point for new researchers in the field of image and video compression. New prediction techniques that go beyond the standardized compression technologies are then presented and discussed. In the context of 3D video, the authors describe a new predictive algorithm for the compression of depth maps, which combines intra-directional prediction, with flexible block partitioning and linear residue fitting. New approaches are described for the compression of Light Field and still images, which enforce sparsity constraints on linear models. The Locally Linear Embedding-based prediction method is investigated for compression of Light Field images based on the HEVC technology. A new linear prediction method using sparse constraints is also described, enabling improved coding performance of the HEVC standard, particularly for images with complex textures based on repeated structures. Finally, the authors present a new, generalized intra-prediction framework for the HEVC standard, which unifies the directional prediction methods used in the current video compression standards, with linear prediction methods using sparse constraints. Experimental results for the compression of natural images are provided, demonstrating the advantage of the unified prediction framework over the traditional directional prediction modes used in HEVC standard. Presents a state-of-the-art review of existing prediction technologies for compression of both 2D and 3D multimedia content; Discusses the most recent advances beyond the current, standardized technologies for image and video compression, such as using the HEVC standard in the context of natural images, 3D and Light Field content; Includes new prediction methods based on alternative techniques and concepts, including flexible block partitioning, linear prediction, sparse representation.
650 0 $a Image compression. $3 660231
650 0 $a Coding theory. $3 532585
650 0 $a Predictive control. $3 667592
650 1 4 $a Engineering. $3 586835
650 2 4 $a Circuits and Systems. $3 896527
650 2 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a Image Processing and Computer Vision. $3 891070
700 1 $a Lucas, Luis Filipe Rosario. $3 3221738
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-51180-1
950 $a Engineering (Springer-11647)