Abstract
In the paper is presented one specific approach aimed at improvement of the visual quality of underexposed or low-contrast medical images. For this are developed adaptive contrast-enhancement algorithms, based on the segmentation of the image area with relatively high density of dark elements. The problem is solved changing the brightness intervals of the selected segments followed by equalization (in particular - linear stretch and skew) of the corresponding parts of the histogram. The implementation is relatively simple and permits easy adaptation of the contrasting algorithms to image contents, requiring setting of small number of parameters only. The corresponding software tools permit to change the image with consecutive steps and to evaluate the visual quality of the processed images. The original image is also available, which permits easy comparison and evaluation. The obtained results prove the efficiency of the new methods for image quality enhancement.
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References
Bovik, A. (ed.): Handbook of Image and Video Processing. Academic Press (2000)
Bow, S.T.: Pattern Recognition and Image Preprocessing. Marcel Dekker (2002)
Pratt, W.: Digital Image Processing. John Wiley and Sons (2001)
Gonzalez, R., Woods, R.: Digital Image Processing. Prentice-Hall (2002)
Sharma, G. (ed.): Digital Imaging Color Handbook. CRC Press, NY (2003)
Kim, Y.: Contrast Enhancement Using Brightness Preserving Bi-Histogram Equalization. IEEE Trans. on Consumer Electronics 43(1), 1–8 (1997)
Jahne, B.: Computer Vision and Applications. Academic Press (2000)
Rowberg, A., Malcolm, B.: Distortion-free Image Contrast Enhancement. In: Inchingolo, P., Pozzi-Mucelli, R. (eds.) EuroPACS-MIR in the Enlarged Europe, pp. 357–360 (2004)
Laihanen, P.: Hue-dependent Contrast Enhancement. Graphic Arts in Finland 30(2), 1–4 (2001)
Chalana, V., Kim, Y.: A Methodology for Evaluation of Boundary Detection Algorithms on Medical Images. IEEE Trans. on Medical Imaging 16(5), 642–652 (1997)
Czerwinski, R., Jones, D., O’Brien, W.: Detection of Lines and Boundaries in Speckle Images -Application to Medical Ultrasound. IEEE Trans. on Medical Imaging 18(2), 126–136 (1999)
Ladak, H., Mao, F., Wang, Y., Steinman, D., Fenster, A., Downey, B.: Prostate Boundary Segmentation from 2D Ultrasound Images. Med. Phys. 17(8), 1–12 (2000)
Milanova, M., Kountchev, R., Todorov, V., Kountcheva, R.: New Method for Lossless Compression of Medical Records. In: Proc. of 8th IEEE Intern. Symp. on Signal Processing and Information Technology (ISSPIT 2008), Bosnia, Herzegovina, pp. 23–28 (2008)
Milanova, M., Kountchev, R., Kountcheva, R., Todorov, V.: Efficient Compression of Sequences of Medical and Multispectral Images. In: SPIE Multiconference, Airborne ISR Systems and Applications, USA, pp. 8020–8031 (2011)
Kountchev, R., Mironov, R., Kountcheva, R.: Efficient Compression of Medical Images Based on Adaptive Histogram Modification. In: Proc. of 46th Int. Conf. on Information, Communication and Energy Systems and Technologies, Serbia, vol. 1(1), pp. 13–16 (2011)
Kountchev, R., Todorov, V., Kountcheva, R.: New Method for Adaptive Lossless Compression of Still Images Based on the Histogram Statistics. In: Tsihrintzis, G.A., Virvou, M., Jain, L.C., Howlett, R.J. (eds.) IIMSS 2011. SIST, vol. 11, pp. 61–70. Springer, Heidelberg (2011)
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Todorov, V., Kountcheva, R. (2013). Adaptive Approach for Enhancement the Visual Quality of Low-Contrast Medical 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_6
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DOI: https://doi.org/10.1007/978-3-319-00029-9_6
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