<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The Depth-Image-Based-Rendering (DIBR) algorithms used for 3D video applications introduce geometric distortions affecting the edge coherency in the synthesized images. In order to better deal with specific geometric distortions in the DIBR synthesized images, we propose full-reference metric based on multi-scale pyramid decompositions using morphological filters. The non-linear morphological filters used in multi-scale image decompositions maintain important geometric information such as edges across different resolution levels. We show that PSNR has particularly good agreement with human judgment when it is calculated between detailed images at higher scales of morphological pyramids. Consequently, we propose reduced morphological pyramid peak signal-to-noise ratio metric (MP-PSNR), taking into account only mean squared errors between pyramids’ images at higher scales. Proposed computationally efficient metric achieves significantly higher correlation with human judgment compared to the state-of-the-art image quality assessment metrics and compared to the tested metric dedicated to synthesis-related artifacts.</p></abstract>

The Depth-Image-Based-Rendering (DIBR) algorithms used for 3D video applications introduce geometric distortions affecting the edge coherency in the synthesized images. In order to better deal with specific geometric distortions in the DIBR synthesized images, we propose full-reference metric based on multi-scale pyramid decompositions using morphological filters. The non-linear morphological filters used in multi-scale image decompositions maintain important geometric information such as edges across different resolution levels. We show that PSNR has particularly good agreement with human judgment when it is calculated between detailed images at higher scales of morphological pyramids. Consequently, we propose reduced morphological pyramid peak signal-to-noise ratio metric (MP-PSNR), taking into account only mean squared errors between pyramids’ images at higher scales. Proposed computationally efficient metric achieves significantly higher correlation with human judgment compared to the state-of-the-art image quality assessment metrics and compared to the tested metric dedicated to synthesis-related artifacts.

Multi–Scale Synthesized View Assessment Based on Morphological Pyramids

Institute for Telecommunications and Electronics IRITEL Beograd, Serbia

University of Novi Sad, Faculty of Technical Sciences, Serbia

Ecole polytechnique de l’Universite de Nantes, IRCCyN Lab, France

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Multi\u2013Scale Synthesized View Assessment Based on Morphological Pyramids"}

The Depth-Image-Based-Rendering (DIBR) algorithms used for 3D video applications introduce geometric distortions affecting the edge coherency in the...

Multi–Scale Synthesized View Assessment Based on Morphological Pyramids

Online veröffentlicht: 17. März 2016

Seitenbereich: 3 - 11

Eingereicht: 07. Sept. 2015

DOI: https://doi.org/10.1515/jee-2016-0001

Schlüsselwörter
morphological pyramid, multiscale PSNR, DIBR image quality assessment

© 2016 Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Multi–Scale Synthesized View Assessment Based on Morphological Pyramids

Online veröffentlicht: 17. März 2016

Seitenbereich: 3 - 11

Eingereicht: 07. Sept. 2015

DOI: https://doi.org/10.1515/jee-2016-0001

Schlüsselwörtermorphological pyramid, multiscale PSNR, DIBR image quality assessment

© 2016 Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
morphological pyramid, multiscale PSNR, DIBR image quality assessment