Removing partial blur in a single image

Shengyang Dai, Ying Wu
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引用次数: 59

Abstract

Removing image partial blur is of great practical importance. However, as existing recovery techniques usually assume a one-layer clear image model, they can not characterize the actual generation process of partial blurs. In this paper, a two-layer image model is investigated. Based on the study of partial blur generation process, a novel recovery technique is proposed for a single input image. Both foreground and background layers are recovered simultaneously with the help of the matting technique, powerful image prior models, and user assistance. The effectiveness of the proposed approach is demonstrated by extensive experiments on image recovery and synthesis on real data.
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去除单个图像中的部分模糊
消除图像局部模糊具有重要的实际意义。然而,由于现有的恢复技术通常假设一个单层的清晰图像模型,它们不能表征部分模糊的实际生成过程。本文研究了一种双层图像模型。在研究局部模糊生成过程的基础上,提出了一种新的单输入图像恢复技术。在消光技术、强大的图像先验模型和用户辅助的帮助下,前景层和背景层同时恢复。在实际数据上进行了大量的图像恢复和合成实验,证明了该方法的有效性。
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