Preservation of image edge feature based on snowfall model smoothing filter

Abstract

Abstract This paper proposed a snowfall model as a novel smoothing filter. The pixel composition of the image was similar to the geographic features, so it could be smooth because of snow accumulation. In the snowfall processing, luminance changes are linked to terrain and snowfall amount. Curvature and luminance gradient decided the amount of snowfall; the amount of snowfall became large on the parts where the curvature was large, and it became little on the parts where the gradient was steep. Snowfall algorithm simulates the natural snowfall process, which nonlinear diffusion and the target feature could be preserved well. Snowfall model has the same function as the Gaussian filter. The number of regions was reduced after Gaussian filter and snowfall model smoothing, respectively. The contrast experiment was carried out based on Watershed algorithm. The image area segmentation that pretreated through snowfall model was compared with Gaussian filter smoothing. The experimental result showed that the proposed snowfall model was a smoothing filter. It was able to realize edge preservation, which was the original purpose, and it was also possible to apply to region segmentation.

Keywords

• Smoothing filter
• Snowfall model
• Edge characteristics
• Image preservation
• Region segmentation