Abstract
Most of the X-ray images are no truly isotropic and its quality varies depending on penetration of X-rays in different anatomical structures and on the technologies of their obtaining. The noise problem arises from the fundamentally statistical nature of photon production. This paper presents an approach for X-ray image enhancement based on contrast limited adaptive histogram equalization (CLAHE), following by morphological processing and noise reduction, based on the Wavelet Packet Decomposition and adaptive threshold of wavelet coefficients in the high frequency sub-bands of the shrinkage decomposition. Implementation results are given to demonstrate the visual quality and to analyze some objective estimation parameters in the perspective of clinical diagnosis.
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References
Smith, M., Docef, A.: Transforms in telemedicine applications. Kluwer Academic Publishers (1999)
Parven, N.R., Sathik, M.: Enhancement of bone fracture by equalization methods. In: Proc. of the Conference on Computer Technology and Development, pp. 391–394. IEEE Xplore Press, Kota Kinabalu (2009)
Zeyong, Aviyente, S.: Image denoising based on the wavelet co-occurrence matrix. IEEE Trans. on Image Processing 9(9), 1522–1531 (2000)
Georgieva, V.: Computed Tomography Images Enhancement with Morphology- based Filters. Proceedings of TU-Sofia 58(1), 128–134 (2008)
Xu, Z., Lin, X., Chen, X.: For removal from video sequences using contrast limited histogram equalization. In: Proceedings of the International Conference on Computational Intelligence and Software Engineering, pp. 1–4. IEEE Xplore Press, Wuhan (2009)
Ali, M.: Realization of CLAHE for Real-time Image Enhancement. Journal of VLSI Signal Processing 38, 35–44 (2004)
Coifmann, R., Wickerhauser, M.: Entropy based Algorithms for best basis selection. IEEE Transaction on information theory 38, 713–718 (1992)
Georgieva, V., Kountchev, R.: An influence of the wavelet packet decomposition on noise reduction in ultrasound images. In: Proceedings of International Scientific Conference on Information, Communication and Energy Systems and Technology, Sofia, Bulgaria, pp. 185–188 (2006)
MATLAB User’s Guide, http://www.mathworks.com
Fayad, L., Jin, Y., Laine, A., Berkmen, Y., Pearson, G., Feedman, B., Heerturn, R.: Chest CT with multiscale Adaptive Histogram Equalization. Radiology 233(3), 845–852 (2002)
Saleh, H., Ahmed, S., Nordin, M.: Improving Diagnostic Viewing of medical Images using Enhancement Algorithms. Journal of Computer Science 7(12), 1831–1838 (2011)
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Georgieva, V., Kountchev, R., Draganov, I. (2013). An Adaptive Enhancement of X-Ray Images. In: Kountchev, R., Iantovics, B. (eds) Advances in Intelligent Analysis of Medical Data and Decision Support Systems. Studies in Computational Intelligence, vol 473. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00029-9_7
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DOI: https://doi.org/10.1007/978-3-319-00029-9_7
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00028-2
Online ISBN: 978-3-319-00029-9
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