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Shading correction for endoscopic images using principal color components

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

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.

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References

  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

    Google Scholar 

  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. Cheng SC, Hsia SC (2003) Fast algorithms for color image processing by principal component analysis. J Vis Commun Image Represent 14(2):184–203. doi:10.1016/S1047-3203(03)00024-5

  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):579–592

    Article  CAS  PubMed  Google Scholar 

  7. Likar Maintz (2000) Viergever, Pernuš: retrospective shading correction based on entropy minimization. J Microsc 197(3):285–295. doi:10.1046/j.1365-2818.2000.00669.x

    Article  CAS  PubMed  Google Scholar 

  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. Tomaževič D, Likar B, Pernuš F (2002) Comparative evaluation of retrospective shading correction methods. J Microsc 208(3):212–223. doi:10.1046/j.1365-2818.2002.01079.x

    Article  PubMed  Google Scholar 

  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 91–109

    Chapter  Google Scholar 

  15. Weibel T, Daul C, Wolf D, Rösch R, Guillemin F (2012) Graph based construction of textured large field of view mosaics for bladder cancer diagnosis. Pattern Recognit 45(12):4138–4150. doi:10.1016/j.patcog.2012.05.023

    Article  Google Scholar 

  16. Young IT, Gerbrands JJ, Van Vliet LJ (1998) Fundamentals of image processing. Delft University of Technology Delft, The Netherlands

    Google Scholar 

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Authors and Affiliations

  1. Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany

    Tobias Bergen, Thomas Wittenberg & Christian Münzenmayer

Authors
  1. Tobias Bergen
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  2. Thomas Wittenberg
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  3. Christian Münzenmayer
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Corresponding author

Correspondence to Tobias Bergen.

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Conflict of interest

Tobias Bergen, Thomas Wittenberg and Christian Münzenmayer declare that they have no conflict of interest.

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Bergen, T., Wittenberg, T. & Münzenmayer, C. Shading correction for endoscopic images using principal color components. Int J CARS 11, 397–405 (2016). https://doi.org/10.1007/s11548-015-1273-3

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  • DOI: https://doi.org/10.1007/s11548-015-1273-3

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