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System and method for estimating spatially varying defocus blur in a digital image

机译:用于估计数字图像中空间变化的散焦模糊的系统和方法

摘要

An image editing application (or a blur classification module thereof) may automatically estimate a coherent defocus blur map from a single input image. The application may represent the blur spectrum as a differentiable function of radius r, and the optimal radius may be estimated by optimizing the likelihood function through a gradient descent algorithm. The application may generate the spectrum function over r through polynomial-based fitting. After fitting, the application may generate look-up tables to store values for the spectrum and for its first and second order derivatives, respectively. The use of these tables in the likelihood optimization process may significantly reduce the computational costs of a given blur estimation exercise. The application may minimize an energy function that includes a data term, a smoothness term, and a smoothness parameter that is adaptive to local image content. The output blur map may be used for image object depth estimation.
机译:图像编辑应用程序(或其模糊分类模块)可以从单个输入图像自动估计相干的散焦模糊图。该应用可以将模糊频谱表示为半径r的可微函数,并且可以通过使用梯度下降算法优化似然函数来估计最佳半径。应用程序可以通过基于多项式的拟合在r上生成频谱函数。拟合后,应用程序可以生成查找表以分别存储频谱值及其一阶和二阶导数。在似然性优化过程中使用这些表可以显着减少给定模糊估计练习的计算成本。该应用可以最小化包括数据项,平滑度项和适应于局部图像内容的平滑度参数的能量函数。输出的模糊图可以用于图像对象深度估计。

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