Abstract
In hybrid 3D endoscopy, range data is used to augment photometric information for minimally invasive surgery. As range sensors suffer from a rough spatial resolution and a low signal-to-noise ratio, subpixel motion between multiple range images is used as a cue for superresolution to obtain reliable range data. Unfortunately, this method is sensitive to outliers in range images and the estimated subpixel displacements. In this paper, we propose an outlier detection scheme for robust super-resolution. First, we derive confidence maps to identify outliers in the displacement fields by correlation analysis of photometric data. Second, we apply an iteratively re-weighted least squares algorithm to obtain the associated range confidence maps. The joint confidence map is used to obtain super-resolved range data. We evaluate our approach on synthetic images and phantom data acquired by a Time-of-Flight/RGB endoscope. Our outlire detection improves the median peak-signal-tonoise ratio by 1.1 dB.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Haase S, Forman C, Kilgus T, et al. ToF/RGB sensor fusion for 3-D endoscopy. Curr Med Imaging Rev. 2013;9:113–9.
Park SC, Park MK, Kang MG. Super-resolution image reconstruction: a technical overview. IEEE Signal Process Mag. 2003;20(3):21–36.
Wetzl J, Taubmann O, Haase S, et al. GPU-Accelerated time-of-flight superresolution for image-guided surgery. Proc BVM. 2013; p. 21–6.
K¨ohler T, Haase S, Bauer S, et al. ToF meets RGB: novel multi-sensor superresolution for hybrid 3-D Endoscopy. Proc MICCAI. 2013;8149:139–46.
Farsiu S, Robinson MD, Elad M, et al. Fast and robust multiframe super resolution. IEEE Trans Image Process. 2004;13(10):1327–44.
Zhao W, Sawhney HS. Is super-resolution with optical flow feasible? Proc ECCV. 2002;2350:599–613.
Scales JA, Gersztenkorn A. Robust methods in inverse theory. Inverse Probl. 1988;4(4):1071–91.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Köhler, T. et al. (2014). Outlier Detection for Multi-Sensor Super-Resolution in Hybrid 3D Endoscopy. In: Deserno, T., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2014. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54111-7_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-54111-7_20
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54110-0
Online ISBN: 978-3-642-54111-7
eBook Packages: Computer Science and Engineering (German Language)