Reliability-based Mesh-to-Grid Image Reconstruction

Koloda J, Seiler J, Kaup A (2016)

Publication Language: English

Publication Type: Conference contribution

Publication year: 2016

Pages Range: 1-5

Conference Proceedings Title: IEEE Workshop on Multimedia Signal Processing (MMSP)

Event location: Montreal CA

ISBN: 978-1-5090-3724-7

DOI: 10.1109/MMSP.2016.7813344

Abstract

This paper presents a novel method for the reconstruction of images from samples located at non-integer positions, called mesh. This is a common scenario for many image processing applications, such as super-resolution, warping or virtual view generation in multi-camera systems. The proposed method relies on a set of initial estimates that are later refined by a new reliability-based content-adaptive framework that employs denoising in order to reduce the reconstruction error. The reliability of the initial estimate is computed so stronger denoising is applied to less reliable estimates. The proposed technique can improve the reconstruction quality by more than 2 dB (in terms of PSNR) with respect to the initial estimate and it outperforms the state-of-the-art denoising-based refinement by up to 0.7 dB.

Authors with CRIS profile

Jan Koloda Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Jürgen Seiler Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Andre Kaup Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS)

How to cite

APA:

Koloda, J., Seiler, J., & Kaup, A. (2016). Reliability-based Mesh-to-Grid Image Reconstruction. In IEEE Workshop on Multimedia Signal Processing (MMSP) (pp. 1-5). Montreal, CA.

MLA:

Koloda, Jan, Jürgen Seiler, and André Kaup. "Reliability-based Mesh-to-Grid Image Reconstruction." Proceedings of the IEEE 18th Workshop on Multimedia Signal Processing (MMSP), Montreal 2016. 1-5.

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