X-Ray Image Enhancement using Global Histogram Equalization

Over the last decade, medical image processing has emerged as an important research area because it is very much sensitive to the naturalistic environments. The principle objective of the image enhancement is to recover the features of the input image. Some factors which make the image enhancement a challenging task. For instance, fluctuation of environmental factors in both training and testing images; and accurate enhancement of the images is required before diagnosis the disease in medical field. Existing methods cause over-amplifying, and occasionally it yields checkerboards of the improved image due to which we may lose the important information in the X-ray image. Therefore, this work implements a simple guideline in order to build small application for medical image enhancement using global histogram equalization that is the enhanced version of histogram equalization technique, which improves the image quality by enlarging the vigorous assortment of the intensity by the histogram of the entire image. The method was tested on publicly available X-ray dataset. The average recognition rate across the dataset specifies the achievement of utilizing the proposed method for image enhancement.