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首页> 外文期刊>International Journal of Advanced Robotic Systems >Gradient-guided color image contrast and saturation enhancement
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Gradient-guided color image contrast and saturation enhancement

机译:梯度引导彩色图像对比度和饱和度增强

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摘要

Digital color images are capable of presenting hue, saturation, and brightness perceptions. Therefore, quality improvement of color images should be taken into account to enhance all three stimuli. An effective method is proposed that aims at enriching the colorfulness, vividness, and contrast of color images simultaneously. In this method, color correction based on magnitude stretching is carried out first, image enhancement is then derived from an intensity-guided operation that concurrently improves the contrast and saturation qualities. Furthermore, the proposed methodology mitigates the heavy computational burden arising from the need to transform the source color space into an alternative color space in conventional approaches. Experiments had been conducted using a collection of real-world images captured under various environmental conditions. Image quality improvements were observed both from subjective viewing and quantitative evaluation metrics in colorfulness, saturation, and contrast.
机译:数字彩色图像能够呈现色调,饱和度和亮度感知。因此,应考虑彩色图像的质量改善以增强所有三种刺激。提出了一种有效的方法,旨在同时丰富彩色图像的丰富度,鲜艳度和对比度。在该方法中,首先执行基于幅度拉伸的颜色校正,然后从同时提高对比度和饱和度质量的强度引导操作导出图像增强。此外,所提出的方法可以减轻由于需要在传统方法中将源颜色空间转换为替代颜色空间的繁重计算负担。使用在各种环境条件下捕获的现实世界图像集合进行了实验。观察到从彩色,饱和度和对比度的主观观看和定量评估度量观察到图像质量改进。

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