Abstract: Due to the nonlinearity of the luminance function produced by many medical recording devices, the quality of medical images deteriorates, which creates problems in the visual research work of physicians. X-rays can be taken as an example. This article examines methods of improving the contrast of graphic images methods of improving the quality of X-ray images. The research was carried out in several stages. Attempts were made to increase the contrast of several dozen X-ray images to select the best image brightness using brightness conversion methods in the MATLAB system. Contrast enhancement was observed during the experiments, resulting in the selection of a brightness range corresponding to the visual contrast enhancement. The selection of variables γ for the selected brightness range of the image was performed. The possibilities of the image histogram equalization method were considered. To obtain the best result before performing gamma correction the method of X-ray image histogram equalization is suggested. An enhancement version of this algorithm is presented because of the comparison. Application of the adaptive histogram equalization algorithm with contrast limitation provides a visual effect of improving the contrast of X-ray images. The NIQE and BRISQUE evaluation functions, which do not use reference images, are used to objectively quantify the conversion results.

Omarova G. S, Starovoitov V. V, Aitkozha Zh. Zh, Bekbolatov S, Ostayeva A. B and Nuridinov O, “Application of the Clahe Method Contrast Enhancement of X-Ray Images” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130549

@article{S2022,
title = {Application of the Clahe Method Contrast Enhancement of X-Ray Images},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130549},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130549},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Omarova G. S and Starovoitov V. V and Aitkozha Zh. Zh and Bekbolatov S and Ostayeva A. B and Nuridinov O}
}