(untitled) (International Journal of Engineering and Computer Science, 2013)
: In digital image processing Medical Imaging is one of the most significant application areas. For visualizing and extracting more details from the given image processing of medical images is much more supportive. Several techniques are existing nowadays for enhancing the quality of medical image. Contrast Enhancement is one of the most functional methods for the enhancement of medical images. Various contrast enhancement techniques are in practice, some are as follows: Linear Stretch, Histogram Equalization, Convolution mask enhancement, Region based enhancement, Adaptive enhancement is already available. Based on characteristics of image choices can be done. On comparing my approach with the existing popular approaches of adaptive enhancement and linear stretching, it has been concluded that the proposed technique is giving much better results than the existing ones. Further, the technique is seed dependent so selection of seed is very important in this algorithm. A seed chosen in darker regions will give better results than the seed chosen in brighter region, because it is assumed that user will require enhancing the darker portions of the image. Furthermore, zooming window and edge growing method is used to visualize the edges more precisely which gives an added advantage is to doctors for better perception of X-ray. Keywords: Histogram Equalization, Adaptive, Convolution, Mask, X-Ray, Zooming, Edge Growing