Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
International Journal of Computer Assisted Radiology and Surgery
Published in: International Journal of Computer Assisted Radiology and Surgery 3/2016

01-03-2016 | Original Article

Shading correction for endoscopic images using principal color components

Authors: Tobias Bergen, Thomas Wittenberg, Christian Münzenmayer

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 3/2016

Login to get access

Abstract

Purpose

Inhomogeneous illumination often causes significant shading and vignetting effects in images captured by an endoscope. Most of the established shading correction methods are designed for gray-level images. Only few papers have been published about how to compensate for shading in color images. For endoscopic images with a distinct red coloring, these methods tend to produce color artifacts.

Method

A color shading correction algorithm for endoscopic images is proposed. Principal component analysis is used to calculate an appropriate estimate of the shading effect so that a one-channel shading correction can be applied without producing undesired artifacts.

Results

The proposed method is compared to established YUV and HSV color-conversion-based approaches. It produces superior results both on simulated and on real endoscopic images. Example images of using the proposed shading correction for endoscopic image mosaicking are presented.

Conclusion

A new method for shading correction is presented which is tailored to images with distinct coloring. It is beneficial for the visual impression and further image analysis tasks.
Literature
1.
Bergen T, Nowack S, Münzenmayer C, Wittenberg T (2013) A hybrid tracking approach for endoscopic real-time panorama imaging. Int J Cars 8(Suppl. 1):352–354
2.
Bergen T, Wittenberg T, Münzenmayer C, Chen CCG, Hager GD (2013) A graph-based approach for local and global panorama imaging in cystoscopy. In: Proceedings of SPIE Vol, vol 8671, pp 86,711K–1
3.
Cavalcanti PG, Scharcanski J (2013) Shading correction in human skin color images. In: Image and Video Processing: An Introductory Guide. iConcept Press, USA
4.
5.
Derganc J, Likar B, Pernus F (2001) Shading correction and segmentation of color images. In: Proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis, 2001. ISPA 2001, pp 345–350. doi:10.​1109/​ISPA.​2001.​938653
6.
Hernandez-Mier Y, Blondel W, Daul C, Wolf D, Guillemin F (2010) Fast construction of panoramic images for cystoscopic exploration. Comput Med Imaging Graph 34(7):579–592CrossRefPubMed
7.
8.
Miranda-Luna R, Hernandez-Mier Y, Daul C, Blondel W, Wolf D (2004) Mosaicing of medical video-endoscopic images: data quality improvement and algorithm testing. In: 1st International Conference on Electrical and Electronics Engineering, 2004. (ICEEE), pp 530–535. doi:10.​1109/​ICEEE.​2004.​1433942
9.
Münzenmayer C, Naujokat F, Mühldorfer S, Wittenberg T (2003) Enhancing texture analysis by color shading correction. In: 9. Workshop Farbbildverarbeitung. Zentrum für Bild-und Signalverarbeitung eV,(Ilmenau)
10.
Plataniotis PDKN, Venetsanopoulos PAN (2000) Color spaces. In: Color Image Processing and Applications, Digital Signal Processing. Springer, Berlin, pp 1–49
11.
Tomazevic D, Likar B, Pernus F (2000) A comparison of retrospective shading correction techniques. In: 15th International Conference on Pattern Recognition, 2000. Proceedings, vol 3, pp 564–567. doi:10.​1109/​ICPR.​2000.​903608
12.
13.
Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001, vol 1, pp I–511–I–518. doi:10.​1109/​CVPR.​2001.​990517
14.
Wall ME, Rechtsteiner A, Rocha LM (2003) Singular value decomposition and principal component analysis. In: Berrar DP, Dubitzky W, Granzow M (eds) A practical approach to microarray data analysis. Springer, New York, pp 91–109CrossRef
15.
16.
Young IT, Gerbrands JJ, Van Vliet LJ (1998) Fundamentals of image processing. Delft University of Technology Delft, The Netherlands
Metadata
Title
Shading correction for endoscopic images using principal color components
Authors
Tobias Bergen
Thomas Wittenberg
Christian Münzenmayer
Publication date
01-03-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Computer Assisted Radiology and Surgery / Issue 3/2016
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-015-1273-3

Other articles of this Issue 3/2016

International Journal of Computer Assisted Radiology and Surgery 3/2016 Go to the issue

Original Article

Accuracy of linear drilling in temporal bone using drill press system for minimally invasive cochlear implantation

Original Article

Configuration optimization and experimental accuracy evaluation of a bone-attached, parallel robot for skull surgery

Original Article

A method for the assessment of time-varying brain shift during navigated epilepsy surgery

Original Article

A geometric method for the detection and correction of segmentation leaks of anatomical structures in volumetric medical images

Original Article

Feasibility of automated target centralization in colonoscopy

Original Article

Differential geometry-based techniques for characterization of boundary roughness of pulmonary nodules in CT images