Abstract
Radiographic images are the result of shooting human organs through x-rays for diagnosis. Radiographic images generally still appear blurred making it difficult for medical experts to determine the diagnosis. For example, imagery accompanied by noise, uniform intensity variations due to uneven lighting, or weak in contrast so that the object is very difficult to be separated from the background through binary operations due to too much noise (disturbance or distortion in the image), and others etc. For that image processing is needed to improve from the noise (noise) of the image. The method to improve radiographic image quality is using median filtering method and histogram equalization. The median filtering method provides the ability for excellent noise reduction by observing blurring. In certain sections the Median filter is also good for salt and pepper Noise because of the median nature that away from the black and white through the stage of identifying the pixel values of be noise The histogram equalization improves the contrast of the image through the histogram leveling where a process alters the distribution of gray-level values to an image so that it becomes uniform. The results showed that median filtering method and histogram equalization can be used to improve image quality.
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