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Image matching in Bayer RAW domain to remove ghosting in multi-exposure image fusion

机译:拜耳RAW域中的图像匹配可消除多重曝光图像融合中的重影

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摘要

Multi exposure image fusion is a well-known approach adopted to create High Dynamic Range (HDR) images and emulate the Human Visual System (HVS) using Standard Dynamic Range (SDR) cameras. The main limitation of current multi-exposure image fusion techniques is their inability to compensate for moving objects in a scene and camera shake. Previous attempts to solve camera shake have been able to accurately align the multi-exposure images that have static backgrounds prior to their fusion. Nonetheless, image alignment cannot solve the issue of ghosting artefacts due to moving objects. In this paper, a local motion compensation technique is proposed to efficiently remove ghosting artefacts due to both, camera shake and object movement in the scene. We provide subjective experimental results to demonstrate the ability of proposed method to remove ghosting artefacts in HDR images.
机译:多重曝光图像融合是一种众所周知的方法,可用于创建高动态范围(HDR)图像并使用标准动态范围(SDR)相机模拟人类视觉系统(HVS)。当前的多重曝光图像融合技术的主要局限性在于它们无法补偿场景中的运动物体和相机抖动。先前解决相机抖动的尝试已经能够在融合之前准确对齐具有静态背景的多重曝光图像。然而,图像对准不能解决由于运动物体而引起的重影伪影的问题。在本文中,提出了一种局部运动补偿技术,以有效地消除由于相机抖动和场景中的物体移动而引起的重影伪影。我们提供主观实验结果,以证明所提出的方法能够消除HDR图像中的重影伪影。

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