Sparsity-based defect pixel compensation for arbitrary camera raw images

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Schöberl M, Seiler J, Kasper B, Foessel S, Kaup A
Publication year: 2011
Pages range: 1257-1260
ISBN: 9781457705397


Abstract


In high quality imaging even tiny distortions as small as a single pixel are visible and can not be accepted. Although the production quality of CMOS image sensors is very high, for reasonable yields we still need to accept some defect pixels and clusters of defects in large image sensors. In this paper we will compare compensation algorithms for raw image sensor data. We propose a new approach based on the sparsity assumption that outperforms existing defect compensation algorithms. Furthermore, our proposed interpolation algorithm is universal and not at all adapted to Bayer pattern images. It can directly be applied to any regular color filter pattern or gray scale image. Our examples show, that image sensors with large clusters of defects can still be used for the generation of high quality images. © 2011 IEEE.



FAU Authors / FAU Editors

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


How to cite

APA:
Schöberl, M., Seiler, J., Kasper, B., Foessel, S., & Kaup, A. (2011). Sparsity-based defect pixel compensation for arbitrary camera raw images. (pp. 1257-1260). Prague, CZ.

MLA:
Schöberl, Michael, et al. "Sparsity-based defect pixel compensation for arbitrary camera raw images." Proceedings of the 36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, Prague 2011. 1257-1260.

BibTeX: 

Last updated on 2018-13-12 at 20:50