Rendering fine hair-like objects with Gaussian noise

Abstract

When synthesizing images of fine objects like hair, we usually adopt sub-pixel drawing techniques to improve the image quality. For this paper, we analyzed the statistical features of images of thin lines and found that the distributions of the pixel values tended to be Gaussian. A psychophysical experiment showed that images of stripes with the appropriate Gaussian noise added are perceived to be finer than the original ones. We applied this perceptional property to hair rendering and developed a fast fine hair drawing algorithm.