Intelligent detail enhancement for differently exposed images

F. Kou, Weihai Chen, Xingming Wu, Zhengguo Li
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引用次数: 2

Abstract

Multi-scale exposure fusion is a fast approach to fuse several differently exposed images captured at the same high dynamic range (HDR) scene into a high quality low dynamic range (LDR) image. The fused image is expected to include all details of the input images, however, the details in the brightest and darkest regions are usually not preserved well. Adding details that are extracted from the input images to the fused image is an efficient approach to overcome the problem. In this paper, a fast selectively detail enhancement algorithm is proposed to extract the details in the brightest and darkest regions of the HDR scene and add the extracted details to the fused image. Experimental results show that the proposed algorithm can enhance the details of the fused image much faster than the existing algorithms with comparable or even better visual quality.
智能细节增强不同曝光的图像
多尺度曝光融合是一种将在同一高动态范围(HDR)场景中拍摄的多幅不同曝光图像融合成高质量低动态范围(LDR)图像的快速方法。融合后的图像被期望包含输入图像的所有细节,然而,最亮和最暗区域的细节通常不能很好地保留。将从输入图像中提取的细节添加到融合图像中是克服这一问题的有效方法。本文提出了一种快速选择性细节增强算法,提取HDR场景中最亮和最暗区域的细节,并将提取的细节添加到融合图像中。实验结果表明,该算法能以比现有算法更快的速度增强融合图像的细节,且具有相当甚至更好的视觉质量。
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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