Video Image Cartoonlization Algorithm Based on Shock Filter
Zeng Dong-me · Jisuanji gongcheng · 2014
A video image cartoonlization algorithm based on shock filter is proposed for the problem that the specialty and complexity of the traditional two dimensional cartoon production lead to the low participation of users. The improved shock filter is to cluster the color and eliminate the noise of the color video image, and the Gaussians difference operator is used to detect edges of the image which is filtered by shock filter. Then, color quantization is applied to the image which has been filtered by shock filter. The edge curves and the quantitative image are fused to generate a personalized cartoon image. Experimental results show that compared with the algorithm for cartoon like stylization of image based on the bilateral filter, shock filter proposed by Osher, shock filter proposed by Alvarez and improvement of the shock filter proposed by Osher, this algorithm can produce stronger visual distinctiveness and higher fidelity of cartoon image with more clearly, more complete, more smooth and more continuous edge curves, and it can generate personalized cartoon video automatically through the stylization conversion of a series of images.