Paper Title
Root-Mean-Skewness Bi-Histogram Equalization Method For Contrast Enhancement And Scalable Brightness Preservation For Low- Contrast Asymmetric Images

Abstract
An amalgamation of a new and an old technique is presented in this paper for the purpose of better contrast enhancement and brightness preservation of both low contrast symmetric input image and low contrast asymmetric input image. First of all, we determine whether the input image is a symmetric image or an asymmetric image. The new technique, Root-Mean-Skewness Bi-Histogram Equalization (RMSKBHE) is proposed for the better contrast enhancement of asymmetric input images. The core idea of this approach is to segment the input image’s histogram into two parts based on an average point. This average point is chosen depending on the skewness value and mean value of the input image. A standard variable gamma is taken and if that gamma value is greater than zero, the square-root of the subtraction of the skewness value and mean value is done to produce the average point and similarly the square-root of the addition of skewness value and mean value is done to obtain the average point when the gamma value happens to be less than zero. The average point is termed as Modified Mean (MM). Based on this modified mean the histogram of input image is divided into two parts and histogram equalization (HE) technique is separately applied on both the segments of the input image. Finally after the separate equalization process is complete, the union of those two segments generates a far better contrast enhanced output image with preserved brightness. A verification and test using RMSKBHE on medical image shows an impressive result of the technique for medical and clinical diagnosis