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In medicine, X-ray images are important, on the basis of which medical professionals can obtain necessary information about the internal structures of patients. The diagnosis is determined using the information that has been received. In some cases, it will not be possible to obtain information sufficient for diagnosis from X-ray image. For example, if the radiation is not delivered to the patient in sufficient quantity, the contrast of the medical X-ray image will not meet the requirement, which means that the analysis of the image will be complicated. This does not allow for making an accurate diagnosis. So, when fine-tuning the contrast of the X-ray image, it's important to guide the patient through the initial processing of the X-ray image, sparing them from undergoing a re-examination. The automation of this process requires the use of objective evaluation indicators. The primary objective of this research is to enhance the contrast of X-ray images through the utilization of an algorithm. Additionally, it aims to evaluate the resulting images using the widely recognized RMS (Root Mean Square) evaluation indicator. Furthermore, the research seeks to identify the most effective algorithm or sequence of algorithms based on this evaluation indicator. [ABSTRACT FROM AUTHOR]