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Single-Image Refocusing and Defocusing

机译:单图像重新对焦和散焦

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摘要

In this paper, we present a postprocessing method to tackle the single-image refocusing-and-defocusing problem. The proposed method can accomplish the tasks of focus-map estimation and image refocusing and defocusing. Given an image with a mixture of focused and defocused objects, we first detect the edges and then estimate the focus map based on the edge blurriness, which is depicted explicitly by a parametric model. The image refocusing problem is addressed in a blind deconvolution framework, where the image prior is modeled by using both global and local constraints. In particular, we correct the defocused blurry edges to sharp ones with the aid of the parametric edge model and then render this cue as a local prior to ensure the sharpness of the refocused image. Experimental results demonstrate that the proposed method performs well in producing visually plausible images with different focus effects from a single input.
机译:在本文中,我们提出了一种后处理方法来解决单图像重新聚焦和散焦问题。所提出的方法可以完成聚焦图估计以及图像重新聚焦和散焦的任务。给定包含聚焦对象和散焦对象的混合图像,我们首先检测边缘,然后根据边缘模糊度估计聚焦图,该模糊度由参数模型明确描述。在盲反卷积框架中解决了图像重新聚焦问题,在该框架中,通过使用全局和局部约束对图像先验模型进行建模。特别是,我们借助参数化边缘模型将散焦的模糊边缘校正为清晰的边缘,然后将此提示作为局部渲染,以确保重新聚焦图像的清晰度。实验结果表明,所提出的方法在从单个输入产生具有不同聚焦效果的视觉上合理的图像方面表现良好。

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