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Color contrast enhancement for color night vision based on color mapping

机译:基于颜色映射的彩色夜视色彩对比度增强

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摘要

The increasing availability and deployment of imaging sensors operating in multiple spectral bands has led to a large research effort in image fusion, bringing a lot of pixel-level color fusion algorithms. Color constancy and color contrast are two important topics for color image fusion. However, there is no work considering these two aspects in the meanwhile. The paper focuses on enhancing the color contrast between targets and their backgrounds and maintaining the color constancy. Firstly, a group of visible and infrared images are rendered with natural colors with color contrast enhancement algorithm. Then a color reference palette is derived from source images and their corresponding fused results. To enrich this palette, the nearest Euclidean distance determines the absent colors. The complete palette can be deployed in real-time to different multi-band image sequences of similar scenes. Experimental results based on different data sets show that the targets are popped out with intense colors while backgrounds present natural color appearance. Some objective analysis also shows that the presented method not only inherits more detail information from source images but also brings bigger color distance when comparing with the existing algorithms.
机译:在多个光谱带工作的成像传感器的可用性和部署的不断增长,导致在图像融合方面进行了大量研究工作,带来了许多像素级颜色融合算法。色彩恒定性和色彩对比度是彩色图像融合的两个重要主题。但是,同时没有考虑这两个方面的工作。本文着重于增强目标与其背景之间的颜色对比度,并保持颜色恒定性。首先,使用色彩对比增强算法以自然色渲染一组可见和红外图像。然后,从源图像及其对应的融合结果中得出颜色参考调色板。为了丰富此调色板,最接近的欧几里德距离确定了不存在的颜色。完整的调色板可以实时部署到相似场景的不同多波段图像序列。基于不同数据集的实验结果表明,目标以强烈的颜色弹出,而背景呈现自然的颜色外观。客观分析还表明,与现有算法相比,该方法不仅从源图像中继承了更多的细节信息,而且带来了更大的色距。

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