Removing Smoothing Effects for Color Image Segmentation

In this study, we described the effects of image smoothing on image segmentation, introduced a method proposed by Yang et al. For removing smoothing effects (hereafter referred as Yang´s method), and modified this method to solve image segmentation problems. The results showed that Yang´s smoothing method still required further improvements, therefore, two solutions to solving problems related to this method were proposed. In Yang´s method, the researchers only considered removing the effects of central pixels in a mask on mask calculation, neglecting the effects of edge pixels in a region of a mask on mask calculation. Therefore, we incorporated an edge mask calculation into Yang´s method. Moreover, in Yang´s method, distinct color masks are contained in the color components of a single pixel, which cause these components to yield differing adjustment results. Thus, the solution to this problem is to adopt a single-colored mask for color adjustments. The experimental results verified that the method proposed in this study effectively improved Yang´s method and removed the effects of smoothing on image segmentation.