In this study, the authors investigate the problem of enhanced image no-reference (NR) quality assessment. For resolving the problem of the enhanced images, it is difficult to obtain reference images, this study proposes an NR image quality assessment (IQA) model based on colour space distribution. Given an enhanced image, our method first uses a gist to select a clear target image in which the scene, colour and quality are similar to the hypothetical reference images. And then, the colour transfer is used between the input images and target images to construct the reference image. Next, the appropriate IQA method is used to assess enhanced image quality. The absolute colour difference and feature similarity (FSIM) are used to measure the colour and grey-scale image quality, respectively. Extensive experiments demonstrate that the proposed method is good at evaluating enhanced image quality for X-ray, dust, underwater and low-light images. The experimental results are consistent with human subjective evaluation and achieve good assessment effects.

中文翻译：

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基于色彩空间分布的增强型图像无参考质量评估

在这项研究中，作者调查了增强图像无参考（NR）质量评估的问题。为了解决增强图像的问题，难以获得参考图像，本研究提出了一种基于色彩空间分布的NR图像质量评估（IQA）模型。给定增强的图像，我们的方法首先使用要点选择清晰的目标图像，其中的场景，颜色和质量类似于假设的参考图像。然后，在输入图像和目标图像之间使用颜色转移来构造参考图像。接下来，使用适当的IQA方法评估增强的图像质量。绝对色差和特征相似度（FSIM）用于分别测量彩色和灰度图像质量。大量实验表明，该方法可以很好地评估X射线，灰尘，水下和弱光图像的增强图像质量。实验结果与人体主观评价相吻合，取得了良好的评价效果。