Super-Resolution for Mixed-Resolution Multiview Image plus Depth Data using a Novel Two-Stage High-Frequency Extrapolation Method for Occluded Areas

Richter T, Seiler J, Schnurrer W, Kaup A (2015)


Publication Language: English

Publication Status: Published

Publication Type: Conference contribution

Publication year: 2015

Journal

Pages Range: 1880-1884

Event location: Quebec City CA

ISBN: 978-1-4799-8339-1

DOI: 10.1109/ICIP.2015.7351127

Abstract

Mixed-resolution multiview setups offer great savings in both, costs regarding the equipment acquisition and complexity refering to data transmission and storage. However, for applications like free viewpoint television, high-resolution images are desired from all available camera perspectives. Therefore, high-frequency information of adjacent high-resolution cameras can be used to increase the visual quality of a low-resolution camera perspective. However, due to occlusions, some parts of the scene are invisible in the high-resolution views and cannot be synthesized from the reference images. In this paper, a novel high-frequency extrapolation method is proposed, utilizing additional sampling points pre-estimated by a low-resolution block-matching approach. Averaged over all considered test sets, the proposed method achieves a PSNR gain of 0.94 dB with respect to the unrefined signal extrapolation algorithm.

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How to cite

APA:

Richter, T., Seiler, J., Schnurrer, W., & Kaup, A. (2015). Super-Resolution for Mixed-Resolution Multiview Image plus Depth Data using a Novel Two-Stage High-Frequency Extrapolation Method for Occluded Areas. In Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP) (pp. 1880-1884). Quebec City, CA.

MLA:

Richter, Thomas, et al. "Super-Resolution for Mixed-Resolution Multiview Image plus Depth Data using a Novel Two-Stage High-Frequency Extrapolation Method for Occluded Areas." Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP), Quebec City 2015. 1880-1884.

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