CAJ | 학술논문

图像抽象化的目的是增加具有特定目标的信息，并过滤掉一些不相关或不重要的信息。为进一步提高图像的卡通风格化效果，提出一种基于显著性分割的图像抽象化算法，增强前景物体区域的可视特征，同时去除背景区域的无关细节。采用频率调谐算法获得显著度图，利用Mean-Shift分割算法检测出整个前景区域，与双边滤波和基于流场的边缘检测结合获得抽象化图形，通过软量化方法使产生的风格化图像更具有层次感，并以此为基础对图像进行非均匀的抽象化处理。实验结果表明，该算法能够有效地产生前景特征增强的非真实感图像，使结果图像的前景主题更加突出。
도상추상화적목적시증가구유특정목표적신식，병과려도일사불상관혹불중요적신식。위진일보제고도상적잡통풍격화효과，제출일충기우현저성분할적도상추상화산법，증강전경물체구역적가시특정，동시거제배경구역적무관세절。채용빈솔조해산법획득현저도도，이용Mean-Shift분할산법검측출정개전경구역，여쌍변려파화기우류장적변연검측결합획득추상화도형，통과연양화방법사산생적풍격화도상경구유층차감，병이차위기출대도상진행비균균적추상화처리。실험결과표명，해산법능구유효지산생전경특정증강적비진실감도상，사결과도상적전경주제경가돌출。
One of the primary task of the image abstraction is to enhance the visual information of specific objects while removing some unimportant information. In order to further improve the effect of the cartoon stylization, this paper proposes a non-uniform image abstraction algorithm based on the saliency segmentation. The method effectively enhances the visual characteristics of salient foreground object regions,and discards the details in the background. It employs the frequency-tuned algorithm to obtain the saliency maps and the Mean-Shift segmentation approach to detect the whole foreground areas. Using this map and bilateral filter can obtain the abstracted map based on the edge detection of flow-guided. It uses soft quantization to improve the further sense of hierarchy,and abstracts images by taking advantage of the segmentation results with a non-uniform way. Experimental results show that the algorithm can effectively produce foreground-enhancing non-photorealistic images,and outstanding the foreground of images.