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Robust artifact-free high dynamic range imaging of dynamic scenes

机译:动态场景的稳健,无伪影的高动态范围成像

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摘要

The irradiance range of the real-world scene is often beyond the capability of digital cameras. Therefore, High Dynamic Range (HDR) images can be generated by fusing images with different exposure of the same scene. However, moving objects pose the most severe problem in the HDR imaging, leading to the annoying ghost artifacts in the fused image. In this paper, we present a novel HDR technique to address the moving objects problem. Since the input low dynamic range (LDR) images captured by a camera act as static linear related backgrounds with moving objects during each individual exposures, we formulate the detection of foreground moving objects as a rank minimization problem. Meanwhile, in order to eliminate the image blurring caused by background slightly change of LDR images, we further rectify the background by employing the irradiances alignment. Experiments on image sequences show that the proposed algorithm performs significant gains in synthesized HDR image quality compare to state-of-the-art methods.
机译:现实世界中的照度范围通常超出了数码相机的能力范围。因此,可以通过融合具有相同场景不同曝光的图像来生成高动态范围(HDR)图像。但是,运动的物体在HDR成像中构成最严重的问题,导致在融合图像中出现令人讨厌的重影伪影。在本文中,我们提出了一种新颖的HDR技术来解决运动物体问题。由于相机捕获的输入低动态范围(LDR)图像在每个单独的曝光过程中均与移动对象充当静态线性相关背景,因此我们将前景移动对象的检测公式化为等级最小化问题。同时,为了消除由LDR图像的背景轻微变化引起的图像模糊,我们通过采用辐照度对齐进一步校正背景。图像序列实验表明,与最新方法相比,该算法在合成的HDR图像质量上具有显着的提高。

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