Intensity mapping function based weighted frame averaging for high dynamic range imaging

W. Yao, Z. Li, S. Rahardja
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引用次数: 3

Abstract

A high quality image can be synthesized by combining several differently exposed low dynamic range (LDR) images of the same scene. For scenes under low lighting condition, cameras are usually set to high sensitivity mode to reduce exposure times and avoid motion blur on captured images. However, those images tend to be noisy and the noise severely degrades the visual quality of final image especially on dark areas. In this paper, a weighted frame averaging method based on an intensity mapping function (IMF) is proposed to reduce noise from the input LDR images with shorter exposures. The proposed method does not require any knowledge on either camera response functions (CRFs) or exposure times, and it is much simpler than the state-of-art method. Experiment results also show that the proposed method effectively removes the noise from the shortly exposed LDR images without introducing any blurring or other artifacts.
基于强度映射函数的高动态范围成像加权帧平均
将同一场景的多张不同曝光的低动态范围(LDR)图像组合在一起可以合成出高质量的图像。在光线不足的情况下,相机通常设置为高感光度模式,以减少曝光时间,避免拍摄的图像出现运动模糊。然而,这些图像往往有噪声,噪声严重降低了最终图像的视觉质量,特别是在黑暗区域。本文提出了一种基于强度映射函数(IMF)的加权帧平均方法来降低短曝光LDR图像的噪声。该方法不需要任何有关相机响应函数(CRFs)或曝光时间的知识,并且比最先进的方法简单得多。实验结果还表明,该方法能够有效地去除短曝光LDR图像中的噪声,且不会引入任何模糊或其他伪影。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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