An Image Fuzzy Enhancement Adopting Linear Membership Function

Abstract

S.K.Pal's fuzzy set theory has been used to deal with the degraded image, wherein the image edges are uncertain and inaccurate. But Pals algorithm losses low grey level information of the original image and the grayscales of the image can not be extended. A fuzzy image enhancement based on linear membership function is proposed through the analysis of classical Pal's fuzzy enhancement. This algorithm avoids the lost of low grades information of the image as well as increases the image's whole grey scales. It is very suited for low grades, low contrast images such as X-ray images. As a result of the linear transformation comparing with Pal's non-linear scheme, the image processing speed is also improved. Experiment results show that the proposed method outperforms traditional Pal's in terms of contrast stretching effect and speed.