Autofocus on Depth of Interest for 3D Image Coding

Joint Authors

EL Falou, W.
Samrouth, Khouloud
Liu, Yi
Déforges, Olivier
Khalil, M.

Source

Journal of Electrical and Computer Engineering

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-02-22

Country of Publication

Egypt

No. of Pages

15

Main Subjects

Information Technology and Computer Science

Abstract EN

For some 3D applications, one may want to focus on a specific depth zone representing a region of interest in the scene.

In this context, we introduce a new functionality called “autofocus” for 3D image coding, exploiting the depth map as an additional semantic information provided by the 3D sequence.

The method is based on a joint “Depth of Interest” (DoI) extraction and coding scheme.

First, the DoI extraction scheme consists of a precise extraction of objects located within a DoI zone, given by the viewer or deduced from an analysis process.

Then, the DoI coding scheme provides a higher quality for the objects in the DoI at the expense of other depth zones.

The local quality enhancement supports both higher SNR and finer resolution.

The proposed scheme embeds the Locally Adaptive Resolution (LAR) codec, initially designed for 2D images.

The proposed DoI scheme is developed without modifying the global coder framework, and the DoI mask is not transmitted, but it is deduced at the decoder.

Results showed that our proposed joint DoI extraction and coding scheme provide a high correlation between texture objects and depth.

This consistency avoids the distortion along objects contours in depth maps and those of texture images and synthesized views.

American Psychological Association (APA)

Samrouth, Khouloud& Déforges, Olivier& Liu, Yi& Khalil, M.& EL Falou, W.. 2017. Autofocus on Depth of Interest for 3D Image Coding. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1175464

Modern Language Association (MLA)

Samrouth, Khouloud…[et al.]. Autofocus on Depth of Interest for 3D Image Coding. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1175464

American Medical Association (AMA)

Samrouth, Khouloud& Déforges, Olivier& Liu, Yi& Khalil, M.& EL Falou, W.. Autofocus on Depth of Interest for 3D Image Coding. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1175464

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1175464