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A new gradient-driven inpainting approach

机译:一种新的渐变驱动的修复方法

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摘要

To the large-scale region geometric inpainting of the digital image, the gradient-driven computing model is superior to previous other models, but its performance is not stable to different inpainted objects because the information propagating direction is uncertain in the inpainting process. In this paper, a novel conclusion is firstly described that it is decisive to the inpainting result that the information propagating direction always points to the outside of inpainted region. Finally, a new method of gradient-driven image inpainting is proposed. Experimental results prove that the method can stabilize the information propagating direction of the inpainting process and its inpainting performance is more robust.
机译:对于数字图像的大规模区域几何修复,梯度驱动的计算模型优于先前的其他模型,但是由于在修复过程中信息传播的方向不确定,因此其性能对于不同的修复对象不稳定。本文首先描述了一个新颖的结论,即信息传播方向总是指向被修复区域的外部,这对修复结果具有决定性作用。最后,提出了一种新的梯度驱动图像修复方法。实验结果证明,该方法可以稳定修复过程的信息传播方向,并且修复性能更强。

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