Joint Regression Modeling and Sparse Spatial Refinement for High-Quality Reconstruction of Distorted Color Images

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Genser N, Seiler J, Kaup A
Publication year: 2019
Language: English


Abstract

High quality algorithms are demanded to reconstruct distorted color images in a variety of applications. For example, distortions can result during transmission over lossy channels in image coding or in multi-view imaging scenarios. In general, not all color channels are equally affected and the losses distribute differently in-between channels. However, state-of-the-art methods process color channels independently and do not take the cross color information into account. Thus, a novel and powerful reconstruction algorithm is formulated in this contribution that exploits color as well as spatial information. Therefore, an initial model is estimated for the distorted area using a reference channel. Then, its quality is estimated and a spatial weighting model is set-up. Afterwards, the initial inter channel prediction is refined by generating a sparse model that takes the spatial correlations into account, as well. Consequently, the proposed method achieves an outstanding quality compared to state-of-the-art methods.


FAU Authors / FAU Editors

Genser, Nils
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Kaup, André Prof. Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Seiler, Jürgen PD Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


How to cite

APA:
Genser, N., Seiler, J., & Kaup, A. (2019). Joint Regression Modeling and Sparse Spatial Refinement for High-Quality Reconstruction of Distorted Color Images. In Proceedings of the IEEE International Conference on Image Processing (ICIP). Taipei, TW.

MLA:
Genser, Nils, Jürgen Seiler, and André Kaup. "Joint Regression Modeling and Sparse Spatial Refinement for High-Quality Reconstruction of Distorted Color Images." Proceedings of the IEEE International Conference on Image Processing (ICIP), Taipei 2019.

BibTeX: 

Last updated on 2019-02-07 at 09:23