Modified luminance based MSR for fast and efficient image enhancement

Li Tao, V. Asari
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引用次数: 65

Abstract

A luminance based multi scale retinex (LB/spl I.bar/MSR) algorithm for the enhancement of darker images is proposed in this paper. The new technique consists only the addition of the convolution results of 3 different scales. In this way, the color noise in the shadow/dark areas can be suppressed and the convolutions with different scales can be calculated simultaneously to save CPU time. Color saturation adjustment for producing more natural colors is implemented. Each spectral band can be adjusted based on the enhancement of the intensity of the band and by using a color saturation parameter. The color saturation degree can be automatically adjusted according to different types of images by compensating the original color saturation in each band. Luminance control is applied to prevent the unwanted luminance drop at the uniform luminance areas by automatically detecting the luminance drop and keeping the luminance up to certain level that is evaluated from the original image. Down-sized convolution is used for fast processing and then the result is re-sized back to the original size. Performance of the new enhancement algorithm is tested in various images captured at different lighting conditions. It is observed that the new technique outperforms the conventional MSR technique in terms of the quality of the enhanced images and computational speed.
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改进的基于亮度的MSR,用于快速有效的图像增强
提出了一种基于亮度的多尺度retinex (LB/spl I.bar/MSR)算法,用于较暗图像的增强。新技术只包括3个不同尺度的卷积结果的相加。这样可以抑制阴影/黑暗区域的颜色噪声,同时计算不同尺度的卷积,节省CPU时间。色彩饱和度调整,以产生更自然的色彩。每个光谱波段可以根据波段强度的增强和使用色彩饱和度参数进行调整。通过补偿每个波段的原始色彩饱和度,可以根据不同类型的图像自动调整色彩饱和度。亮度控制是通过自动检测亮度下降,并将亮度保持在原图像评估的一定水平,防止均匀亮度区域出现不需要的亮度下降。减小大小的卷积用于快速处理,然后将结果重新调整到原始大小。在不同光照条件下拍摄的不同图像中测试了新增强算法的性能。结果表明,该方法在增强图像质量和计算速度方面优于传统的MSR技术。
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