Paper Info
Title
Tuned depth signal analysis on merged transform domain for view synthesis in free viewpoint systems
Abstract
Completely embedded in the 3D era, depth maps coding becomes a must in order to favour 3D admission to different fields of application, ranging from video games to medical imaging. This study presents a novel depth coding approach that, after a decimation step favouring the foreground, decomposes depth maps onto a set of sparse coefficients and redundant mixed discrete cosine and B-splines atoms highly correlated to depth maps piece-wise linear nature. Depth decomposition searches the best rate/distortion tradeoff through minimisation of an adaptive cost function, where its weight parameter is manipulated according to depth homogeneity. The bigger the parameter is, the more the sparsity is favoured at the expense of synthesis quality. Furthermore, handled distortion measure of the cost function quantifies the effect of depth maps coding on rendered views quality. The experiments show the relevance of the proposed method, able to obtain considerable tradeoffs between bitrate and synthesised views distortion.
Year
DOI
Venue
2015
10.1049/iet-ipr.2013.0516
Image Processing, IET  
Keywords
Field
DocType
discrete cosine transforms,signal synthesis,video coding,3d admission,b-splines atoms,adaptive cost function,depth decomposition,depth homogeneity,depth maps coding,discrete cosine,free viewpoint systems,medical imaging,merged transform domain,novel depth coding approach,piecewise linear nature,quality synthesis,sparse coefficients,tuned depth signal analysis,video games,view synthesis
Computer vision,Signal processing,Decimation,Homogeneity (statistics),Pattern recognition,Coding (social sciences),View synthesis,Minimisation (psychology),Ranging,Artificial intelligence,Distortion,Mathematics
Journal
Volume
Issue
ISSN
9
3
1751-9659
Citations 
PageRank 
References 
0
0.34
20
Authors
3
Name
Order
Citations
PageRank
Faten Chaieb1275.23
Dorsaf Sebai242.78
Faouzi Ghorbel336146.48