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Detail-enhanced fusion of differently exposed images

机译:不同曝光图像的细节增强融合

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摘要

In a typical processing chain of an image enhancement, an exposure fusion scheme can be used which usually includes smoothing effect which allows prevention of occurrence of seams in the final image. But such step usually comes with a price of losing fine details thereby blurring the final image, which then makes the scheme unable to preserve fine details as good as high dynamic range (HDR) imaging schemes. In this paper, we introduce a new quadratic optimization based method to extract fine details from a vector field. The new method extracts fine details from a set of differently exposed low dynamic range (LDR) images simultaneously. The extracted details are then added to an intermediate image that is fused by simply using an existing exposure fusion scheme. With this, the proposed scheme can preserve fine details as good as a normal HDR imaging scheme.
机译:在图像增强的典型处理链中,可以使用曝光融合方案,该方案通常包括平滑效果,该平滑效果允许防止在最终图像中出现接缝。但是,这样的步骤通常会带来损失细节的代价,从而使最终图像模糊,这使得该方案无法像高动态范围(HDR)成像方案一样保留细节。在本文中,我们介绍了一种基于二次优化的新方法,可从矢量场中提取细节。新方法同时从一组不同曝光的低动态范围(LDR)图像中提取精细细节。然后将提取的细节添加到仅通过使用现有曝光融合方案进行融合的中间图像上。这样,所提出的方案可以保留与普通HDR成像方案一样好的细节。

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