Wang Shuhang, Cho Woon, Jang Jinbeum, Abidi Mongi A, Paik Joonki
J Opt Soc Am A Opt Image Sci Vis. 2017 Jan 1;34(1):7-17. doi: 10.1364/JOSAA.34.000007.
Outdoor images captured in bad-weather conditions usually have poor intensity contrast and color saturation since the light arriving at the camera is severely scattered or attenuated. The task of improving image quality in poor conditions remains a challenge. Existing methods of image quality improvement are usually effective for a small group of images but often fail to produce satisfactory results for a broader variety of images. In this paper, we propose an image enhancement method, which makes it applicable to enhance outdoor images by using content-adaptive contrast improvement as well as contrast-dependent saturation adjustment. The main contribution of this work is twofold: (1) we propose the content-adaptive histogram equalization based on the human visual system to improve the intensity contrast; and (2) we introduce a simple yet effective prior for adjusting the color saturation depending on the intensity contrast. The proposed method is tested with different kinds of images, compared with eight state-of-the-art methods: four enhancement methods and four haze removal methods. Experimental results show the proposed method can more effectively improve the visibility and preserve the naturalness of the images, as opposed to the compared methods.
在恶劣天气条件下拍摄的户外图像通常具有较差的强度对比度和色彩饱和度，因为到达相机的光线会严重散射或衰减。在恶劣条件下提高图像质量的任务仍然是一项挑战。现有的图像质量改进方法通常对一小部分图像有效，但对于更广泛的各种图像往往无法产生令人满意的结果。在本文中，我们提出了一种图像增强方法，该方法通过使用内容自适应对比度改进以及依赖于对比度的饱和度调整来增强户外图像。这项工作的主要贡献有两个方面：（1）我们基于人类视觉系统提出了内容自适应直方图均衡化来提高强度对比度；（2）我们引入了一种简单而有效的先验方法，根据强度对比度来调整色彩饱和度。我们用不同类型的图像对所提出的方法进行了测试，并与八种最新方法进行了比较：四种增强方法和四种去雾方法。实验结果表明，与比较方法相比，所提出的方法可以更有效地提高图像的可见性并保持图像的自然度。
