Novel Weighted Mean Separated Histogram Equalization for Contrast Enhancement of Underwater Images
S. A. Hariprasad, Vikhar Ahmed · 2013
Abstract — Underwater acoustic is growing interest because of its applications in scientific research and technology. Its applications such as mine detection, marine biology and military operations requires a high quality of images. In underwater environment, quality of image is degraded by scattering of light and absorption of light which results in low contrast, poor visibility, blurring of image. Histogram equalization (HE) is the conventional method of enhancing the contrast of an image, but HE creates unwanted visual artifacts, which lead to over enhancement of image, loss of image details and loss of natural look of image. Recursively Mean Separated Histogram Equalization (RMSHE) is one of the modifications to HE to overcome from the limitations of HE. This method will reduce the visual artifacts and enhance the contrast of image but still there is a loss of image details. In this paper a modified RMSHE referred as Weighted Mean Separated Histogram Equalization (WMSHE) is presented which will enhance the contrast of image along with reduction of visual artifacts. The method preserves image details and brightness. In this method Histogram is divided into four sub-Histograms based on weighted mean value and then apply clipping limit to each sub-Histogram followed by equalization of each sub-Histogram. Performance of the algorithm is measured in terms of Absolute Mean Brightness Error (AMBE), Entropy of image and difference in Standard Deviation (SD). It is found that with proposed method AMBE is improved by 52.57%, SD is improved by 39.64 % as compared to RMSHE, and Entropy of image with proposed method is 6.6221 whereas Entropy with RMSHE is 6.4746.