Medical Image Enhancement Using Histogram Processing Techniques Followed by Median Filter

Contrast enhancement plays a key role in analyzing medical images taken through different diagnosing methods (like CT scan, X-ray and MRI) especially in biomedical applications and secures digital image transmission. The principle objective of image enhancement technique is to improve the characteristics or quality of an input image. To improve the image contrast, numerous enhancement techniques have been proposed in literature and the conventional methods include Global Histogram Equalization (GHE), Local Histogram Equalization (LHE) techniques etc. However, the main limitations of these techniques are unpleasant visual artifacts such as over enhancement, level saturation and raised noise level. To overcome these, researchers suggested techniques like Brightness Preserving Bi-Histogram Equalization (BBHE) and Dualistic Sub-Image Histogram Equalization (DSIHE) which failed to eliminate the impulse noise. In this paper, the low contrast noisy medical images are preprocessed for image enhancement followed by noise reduction phase through filtering to reconstruct the original image. Various well-known contrast enhancement techniques like GHE, LHE, BBHE and DSIHE followed by median filter are implemented and their comparative performance analyzed using subjective and objective image quality parameters.