基于Mean Shift和FDoG的图像卡通化渲染

针对现有图像卡通化渲染算法区域划分不明显或提取的边界不够连贯的问题，提出了一种基于Mean Shift和FDoG的图像卡通化渲染方法。该方法通过区域分割与边界处理相融合的手段，获取区域明晰、边界光滑连贯的卡通对象，同时结合亮度量化策略等后处理技术净化对象，最终获得具有卡通效果的图像。渲染算法采用Mean Shift技术对图像进行分割，通过设置合适的参数获取若干有意义的区域；引入FDoG算法思想对图像边界进行分析和提取；最后去除或合并视觉上的干扰区域，并参考卡通画的亮度分布特点对图像进行亮度量化，得到最终的卡通风格图像。方法实现简单，自动化程度较高，实验结果较理想。

Image cartoon style rendering based on Mean Shift and FDoG

Non-smooth extracted boundaries or lack of salient region segmentation are major drawbacks of existing image cartoon style rendering algorithms. To deal with this problem, a cartoon style rendering method based on Mean Shift and FDoG is presented. Given an image, the method acquires a cartoon object with salient segmentation of regions and smoothly connected boundaries from the image by using techniques of both region segmentation and edge extraction, combined with the luminance quantization strategy and other post-processing technologies for cleansing objects to finally generate a cartoon style image. More specifically, the method first segments the image via Mean-shift algorithm into valid regions by setting appropriate parameters, and then adopts FDoG algorithm to extract image edges, and finally gets the final image with cartoon style by removing or merging visually disturbing regions and by quantizing the image’s luminance channel with reference to cartoon image’s luminance distribution. The proposed method is easy to implement and the satisfactory experimental results is gotten.