Comparison of contrast enhancement techniques for medical image

Abstract

The main goal of this paper is to process a medical image. For a medical diagnosis, the result is more suitable. Contrast enhancement is used to improve the contrast of an image. Contrast enhancement of images is used for a different variety of applications such as in the medical field. Most of the images like medical images, remote sensing, aerial images and real life photographs suffer from poor contrast. The main goal of image enhancement is to improve the quality or clarity of images or to increase the interpretability in images for human viewing. In medical images detection and analysis, contrast enhancement techniques are one of the most significant stages. We are used contrast enhancement techniques to achieve contrast enhancement of images. The type of techniques includes neighborhood operation, average filter, bilateral ratinex, imadjust and sigmoid function. All these techniques are comparing with each other to achieve which enhancement techniques have produced a better contrast of an image. The four separate parameters are used. These parameters are such as peak signal to noise ratio (PSNR), mean square error (MSE), normalization coefficient (NC) and root mean square error (RMSE). In image research, this is one of the most important and difficult technique.