In augmented reality scenarios, virtual images observed through optical see-through head-mounted displays (OST-HMDs) contain color distortion due to external light. This phenomenon is known as background color blending. Existing methods to overcome this issue based on background subtraction compensation produce negative values when the background is brighter than the virtual image. In such cases, virtual images lose their structural integrity and image quality deteriorates. To solve this problem, we propose a gamma-curve-based virtual image boosting method. We derive a measurement model to determine the appropriate gamma value for virtual image boosting using empirical data obtained from extensive real experiments featuring a variety of virtual images and backgrounds. These diverse experiments prove that the proposed boosting method can effectively improve background color blending. With diverse combinations of natural virtual images and bright backgrounds, including even colorful backgrounds featuring high color saturation, the proposed boosting method produces visually pleasing image quality.

中文翻译：

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通过用于光学透视显示器的基于伽马的图像增强方法增强减少颜色混合

在增强现实场景中，通过光学透视头戴式显示器 (OST-HMD) 观察到的虚拟图像包含由于外部光线导致的颜色失真。这种现象被称为背景颜色混合。当背景比虚拟图像更亮时，基于背景减法补偿来克服这个问题的现有方法会产生负值。在这种情况下，虚拟图像会失去其结构完整性并且图像质量会下降。为了解决这个问题，我们提出了一种基于伽马曲线的虚拟图像增强方法。我们使用从具有各种虚拟图像和背景的大量真实实验中获得的经验数据推导出一个测量模型，以确定用于虚拟图像增强的适当伽马值。这些不同的实验证明所提出的增强方法可以有效地改善背景颜色混合。通过自然虚拟图像和明亮背景的多种组合，甚至包括具有高色彩饱和度的彩色背景，所提出的增强方法可以产生视觉上令人愉悦的图像质量。