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Contrast enhancement and details preservation of tone mapped high dynamic range images

机译:色调映射的高动态范围图像的对比度增强和细节保留

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This paper proposes a Tone Mapping (TM) approach converting a High Dynamic Range (HDR) image into a Low Dynamic Range (LDR) image while preserving as much information of the HDR image as possible to ensure a good LDR image visual quality. This approach is based on a separable near optimal lifting scheme using an adaptive powerful prediction step. The latter relies on a linear weighted combination depending on the neighboring coefficients extracting then the relevant finest details in the HDR image at each resolution level. Moreover the approximation and detail coefficients are modified according to the entropy of each subband. The pixel's distribution of the coarse reconstructed LDR image is then adjusted according to a perceptual quantizer with respect to the human visual system using a piecewise linear function. Simulation results provide good results, both in terms of visual quality and TMQI metric, compared to existing competitive TM approaches. (C) 2018 Published by Elsevier Inc.
机译:本文提出了一种色调映射(TM)方法,将高动态范围(HDR)图像转换为低动态范围(LDR)图像,同时保留尽可能多的HDR图像信息,以确保良好的LDR图像视觉质量。该方法基于使用自适应强大预测步骤的可分离的接近最佳提升方案。后者依赖于线性加权组合,具体取决于相邻系数的提取,然后提取每个分辨率级别的HDR图像中的相关最佳细节。此外,根据每个子带的熵来修改近似系数和细节系数。然后,使用分段线性函数,根据相对于人类视觉系统的感知量化器,来调整粗略重构的LDR图像的像素分布。与现有的竞争性TM方法相比,仿真结果在视觉质量和TMQI度量方面均提供了良好的结果。 (C)2018由Elsevier Inc.发布

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