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PMSR Model for Low Illumination Image Enhancement

机译:低照度图像增强的PMSR模型

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摘要

Enhancement of low illumination images is of great importance in poor imaging conditions. A new image enhancement model was proposed in this paper. The model divided an image into blocks and used the local standard deviation to design the center/surround filter and utilized amplitude compensation factor to compensate the shortage of logarithmic function in compressing the near-zero data's amplitude. In addition, the amplitude compensation factor can suppress noise. At the same time, the normalized brightness can maintain the normal brightness region of the image while the brightness of the image is increased. In order to verify the performance of the proposed model, the proposed model and existing models are applied to image enhancement. To evaluate its performance in image enhancement, results are compared from the subjective and objective aspects. The experimental results show that the proposed model preserved the image details better and avoided the excessive enhancement of the normal brightness region.
机译:在恶劣的成像条件下,低照度图像的增强非常重要。本文提出了一种新的图像增强模型。该模型将图像分成多个块,并使用局部标准差设计中心/环绕滤波器,并利用幅度补偿因子来补偿对数函数在压缩近零数据幅度时的不足。另外,幅度补偿因子可以抑制噪声。同时,归一化的亮度可以在增加图像的亮度的同时保持图像的正常亮度区域。为了验证所提出模型的性能,将所提出的模型和现有模型应用于图像增强。为了评估其在图像增强方面的性能,从主观和客观方面比较了结果。实验结果表明,提出的模型能够更好地保留图像细节,避免了正常亮度区域的过度增强。

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