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Painterly rendering using image salience

机译:使用图像Parience的画家渲染

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The contribution of this paper is a novel non-photorealistic rendering (NPR) technique, capable of producing an artificial 'hand-painted' effect on 2D images, such as photographs. Our method requires no user interaction, and makes use of image salience and gradient information to determine the implicit ordering and attributes of individual brush strokes. The benefits of our technique are complete automation, and mitigation against the loss of image detail during painting. Strokes from lower salience regions of the image do not encroach upon higher salience regions; this can occur with some existing painting methods. We describe our algorithm in detail, and illustrate its application with a gallery of images.
机译:本文的贡献是一种新型非光电态性渲染(NPR)技术,能够在诸如照片的2D图像上产生人造的“手绘”效果。我们的方法不需要用户交互,并利用图像Parience和梯度信息来确定单个刷子笔划的隐式排序和属性。我们技术的好处是完全自动化,并在绘画期间减轻图像细节的损失。从图像的较低显着区域的冲程不会侵占更高的显着区域;某些现有绘画方法可以发生这种情况。我们详细描述了我们的算法,并用图像图库说明了其应用程序。

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