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Effective gradient domain object editing on mobile devices

机译:在移动设备上有效的梯度域对象编辑

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We present a gradient domain object editing approach and its implementation for mobile devices. It can be used for creating a new composite image by removing, adding, and moving objects in an image. The approach can be divided into two parts: creation and editing of a new gradient vector field, and recovery of a new composite image from the new gradient vector field. In the first part, a new gradient vector field is created from the gradients of the source image, and then updated by inserting the new object gradients, by removing object gradients and filling removed areas with the gradients of best-fit patches found in other parts of the source image, or by combining these two processes when moving objects. In the second part, a divergence vector field is computed from the gradient vector field and used for a guidance vector to construct a Poisson equation. The new composite image is recovered from the gradient vector field by solving the Poisson equation with boundary conditions. Our approach can merge all regions in the picture seamlessly with smooth color transition for the whole picture. It can be used for large object removal and for filling the background of the removed object. The final composite image is a globally optimal solution. The approach is implemented and runs with good performance on mobile camera phones.
机译:我们提出了一种梯度域对象编辑方法及其在移动设备上的实现。通过删除,添加和移动图像中的对象,可以将其用于创建新的合成图像。该方法可以分为两部分:创建和编辑新的梯度矢量场,以及从新的梯度矢量场恢复新的合成图像。在第一部分中,从源图像的梯度创建一个新的梯度矢量场,然后通过插入新的对象梯度,删除对象梯度并用在其他部分中找到的最适合色块的梯度填充已去除的区域来更新该梯度矢量场。源图像的图像,或者在移动对象时将这两个过程结合在一起。在第二部分中,从梯度矢量场计算出散度矢量场,并将其用作引导矢量以构造泊松方程。通过用边界条件求解泊松方程,可以从梯度矢量场中恢复新的合成图像。我们的方法可以无缝合并图像中的所有区域,并为整个图像提供平滑的颜色过渡。它可用于大型物体的去除以及填充被去除物体的背景。最终的合成图像是全局最佳解决方案。该方法已实现并在移动照相手机上以良好的性能运行。

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