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Color gradient vectorization for SVG compression of comic image

机译:用于漫画图像SVG压缩的颜色梯度矢量化

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In past years, different raster-to-vector methods were proposed to convert bitmap images to SVG format. However, they did not consider the color gradient (CG) that frequently appears in the comic image. Their results needed multiple divided color regions to represent a single CG region. It produced poor perceptual quality and large SVG size. In this paper, we propose the CGV (CG vectorization) method to resolve this problem. CGV first applies a linear-time algorithm to identify the CG vector for representing the color and the direction of CG in each region. Then, we merge neighboring regions those have the same CG vector as a large CG region and represent it by a single path of SVG with linear gradient syntax. Experimental results show that our method outperforms other state-of-the-art SVG vectorization systems in terms of not only SVG size but also perceptual quality. For example, the averages SSIM are 0.85 by Autotrace, 0.92 by Autotrace+Merge, 0.88 by SWaterG, 0.91 by Vector Magic and 0.94 by our method. It is about 57.23% for our average space saving. Moreover, comparing with other systems' results, our SVG files take the shortest time (about 0.12 s in average) of rendering on handheld devices. (C) 2015 Elsevier Inc. All rights reserved.
机译:在过去的几年中,提出了不同的栅格到矢量方法将位图图像转换为SVG格式。但是,他们没有考虑漫画图像中经常出现的颜色梯度(CG)。他们的结果需要多个分开的颜色区域来表示单个CG区域。它产生了较差的感知质量和较大的SVG尺寸。在本文中,我们提出了CGV(CG矢量化)方法来解决此问题。 CGV首先应用线性时间算法来识别CG向量,以表示每个区域中CG的颜色和方向。然后,我们合并与大CG区域具有相同CG向量的相邻区域,并使用线性梯度语法通过SVG的单个路径来表示它。实验结果表明,我们的方法不仅在SVG大小方面,而且在感知质量方面都优于其他最新的SVG矢量化系统。例如,根据我们的方法,SSIM的平均值分别为Autotrace的0.85,Autotrace + Merge的0.92,SWaterG的0.88,Vector Magic的0.91和0.94。平均节省空间约为57.23%。此外,与其他系统的结果相比,我们的SVG文件在手持设备上的渲染时间最短(平均约0.12 s)。 (C)2015 Elsevier Inc.保留所有权利。

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