Recurrent pattern matching based stereo image coding using linear predictors

Lucas, Luís F. R.; M. M. Rodrigues, Nuno; Pagliari, Carla L.; Silva, Eduardo A. B. da; Faria, Sérgio M. M. de

Publication

Recurrent pattern matching based stereo image coding using linear predictors

2016-05-02Journal article

dc.contributor.author	Lucas, Luís F. R.
dc.contributor.author	M. M. Rodrigues, Nuno
dc.contributor.author	Pagliari, Carla L.
dc.contributor.author	Silva, Eduardo A. B. da
dc.contributor.author	Faria, Sérgio M. M. de
dc.date.accessioned	2025-05-28T14:14:14Z
dc.date.available	2025-05-28T14:14:14Z
dc.date.issued	2016-05-02
dc.description.abstract	The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based generic image encoding solution which has been investigated earlier for the compression of stereo images with successful results. While first MMP-based proposals for stereo image coding employed dictionary-based techniques for disparity compensation, posterior developments have demonstrated the advantage of using predictive methods. In this paper, we focus on recent investigations on the use of predictive methods in the MMP algorithm and propose a new prediction framework for efficient stereo image coding. This framework comprises an advanced intra directional prediction model and a new linear predictive scheme for efficient disparity compensation. The linear prediction model is the main novelty of this work, combining adaptive linear models estimated by least-squares algorithm with fixed linear models provided by the block-matching algorithm. The performance of the proposed intra prediction and disparity compensation methods when applied in an MMP encoder has been evaluated experimentally. Comparisons with the current stereo image coding standards showed that the proposed MMP algorithm significantly outperforms the Stereo High Profile of H.264/AVC standard. In addition, it presents a competitive performance relative to the MV-HEVC standard. These results also suggest that current stereo image coding standards may benefit from the proposed linear prediction scheme for disparity compensation, as an extension to the omnipresent block-matching solution.	eng
dc.description.sponsorship	This project was funded by FCT—“Fundação para a Ciência e Tecnologia”, Portugal, under the Grant SFRH/BD/79553/2011. This work was partially financed by CAPES/Pro-Defesa under Grant Number 23038.009094/2013-83.
dc.identifier.citation	Lucas, L.F.R., Rodrigues, N.M.M., Pagliari, C.L. et al. Recurrent pattern matching based stereo image coding using linear predictors. Multidim Syst Sign Process 28, 1393–1416 (2017). https://doi.org/10.1007/s11045-016-0417-0
dc.identifier.doi	10.1007/s11045-016-0417-0
dc.identifier.issn	0923-6082
dc.identifier.issn	1573-0824
dc.identifier.uri	http://hdl.handle.net/10400.8/13018
dc.language.iso	eng
dc.peerreviewed	yes
dc.publisher	Springer Science and Business Media LLC
dc.relation	SFRH/BD/79553/2011
dc.relation	23038.009094/2013-83
dc.relation.hasversion	https://link.springer.com/article/10.1007/s11045-016-0417-0
dc.relation.ispartof	Multidimensional Systems and Signal Processing
dc.rights.uri	N/A
dc.subject	Stereo image coding
dc.subject	Pattern matching
dc.subject	Disparity compensation
dc.subject	Linear prediction
dc.subject	Least-squares prediction
dc.subject	Block matching algorithm
dc.title	Recurrent pattern matching based stereo image coding using linear predictors	eng
dc.type	journal article
dspace.entity.type	Publication
oaire.citation.endPage	1416
oaire.citation.issue	4
oaire.citation.startPage	1393
oaire.citation.title	Multidimensional Systems and Signal Processing
oaire.citation.volume	28
oaire.version	http://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyName	M. M. Rodrigues
person.givenName	Nuno
person.identifier.orcid	0000-0001-9536-1017
person.identifier.scopus-author-id	7006052345
relation.isAuthorOfPublication	b4ebe652-7f0e-4e67-adb0-d5ea29fc9e69
relation.isAuthorOfPublication.latestForDiscovery	b4ebe652-7f0e-4e67-adb0-d5ea29fc9e69