计算机工程与应用
計算機工程與應用
계산궤공정여응용
Computer Engineering and Applications
2015年
22期
176-180
,共5页
优化式着色%K最邻近结点算法(KNN)%二次着色%图层信息
優化式著色%K最鄰近結點算法(KNN)%二次著色%圖層信息
우화식착색%K최린근결점산법(KNN)%이차착색%도층신식
optimization-based colorization%K Nearest Neighbors(KNN)%recolorization%layers information
针对灰度图像彩色化技术应用于彩色图像二次着色时往往忽略掉原始图像所带的色彩信息的问题，提出了一种基于KNN图层区分的优化式着色算法。与现有的优化式着色方法相比，该方法一方面采用基于KNN的图像前背景区分算法获得图层区分的图像，生成新的权值函数；另一方面将图层区分结果引入优化式着色方法，并对图像着色。实验结果表明，算法能有效解决物体边界处发生颜色渗漏的问题，得到颜色分布精确的图像。在相同输入前提下，算法可以得到更好的着色结果。
針對灰度圖像綵色化技術應用于綵色圖像二次著色時往往忽略掉原始圖像所帶的色綵信息的問題，提齣瞭一種基于KNN圖層區分的優化式著色算法。與現有的優化式著色方法相比，該方法一方麵採用基于KNN的圖像前揹景區分算法穫得圖層區分的圖像，生成新的權值函數；另一方麵將圖層區分結果引入優化式著色方法，併對圖像著色。實驗結果錶明，算法能有效解決物體邊界處髮生顏色滲漏的問題，得到顏色分佈精確的圖像。在相同輸入前提下，算法可以得到更好的著色結果。
침대회도도상채색화기술응용우채색도상이차착색시왕왕홀략도원시도상소대적색채신식적문제，제출료일충기우KNN도층구분적우화식착색산법。여현유적우화식착색방법상비，해방법일방면채용기우KNN적도상전배경구분산법획득도층구분적도상，생성신적권치함수；령일방면장도층구분결과인입우화식착색방법，병대도상착색。실험결과표명，산법능유효해결물체변계처발생안색삼루적문제，득도안색분포정학적도상。재상동수입전제하，산법가이득도경호적착색결과。
It is possible to recolorize images by applying existing scribble based colorization algorithms for grayscale images, which omitting colors in original images. This paper proposes an optimized method to improve the existing image recolor-ization technologies. In comparison with the optimization-based colorization, the proposed method features in:(i)using K Nearest Neighbors(KNN)to preprocess images into stratified layers and learn from their content to produce a new sim-ulated weight function;(ii)colorizing images in terms of the optimized layer-based weights and hence producing optimized colorizations. Extensive experimental results show that the proposed algorithm can solve the problem of color leakage at the boundary of the object, and obtain accurate color images. Compared with previous methods, the proposed algorithm is more robust to color blending in the input data.
