Reconstruction of multiview images taken with non-regular sampling sensors

Richter T, Jonscher M, Seiler J, Kaup A (2014)


Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2014

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 5789-5793

Article Number: 6854713

Event location: Florence IT

ISBN: 978-1-4799-2893-4

DOI: 10.1109/ICASSP.2014.6854713

Abstract

Increasing spatial image resolution is a widely discussed area in the field of image processing. In this paper, we present an efficient reconstruction approach for high-resolution images, taken with irregularly shielded low-resolution sensors in a multiview setup. The approach is based on the sparsity assumption, meaning that natural images can be efficiently represented in a transform-domain using only few coefficients. Utilizing information from adjacent cameras results in a better reconstruction quality for the central high-resolution view. Since neighboring camera perspectives might differ in illumination, the information from adjacent views has to be adapted to the view to be reconstructed. The simulation results show that a proper incorporation of information from neighboring views leads to a PSNR gain of up to 2.20 dB compared to a state-of-the-art singleview reconstruction approach. © 2014 IEEE.

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How to cite

APA:

Richter, T., Jonscher, M., Seiler, J., & Kaup, A. (2014). Reconstruction of multiview images taken with non-regular sampling sensors. In Proceedings of the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 (pp. 5789-5793). Florence, IT: Institute of Electrical and Electronics Engineers Inc..

MLA:

Richter, Thomas, et al. "Reconstruction of multiview images taken with non-regular sampling sensors." Proceedings of the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence Institute of Electrical and Electronics Engineers Inc., 2014. 5789-5793.

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