...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Image Processing, IET >Enhanced image no-reference quality assessment based on colour space distribution
【24h】

Enhanced image no-reference quality assessment based on colour space distribution

机译：基于颜色空间分布的增强图像无参考质量评估

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

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.
机译：在这项研究中，作者研究了增强图像无参考（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，本研究提出了基于颜色空间分布的NR图像质量评估（IQA）模型。给定增强图像，我们的方法首先使用要点选择一个清晰的目标图像，其中场景，颜色和质量类似于假设参考图像。然后，在输入图像和目标图像之间使用颜色传输以构建参考图像。接下来，使用适当的IQA方法来评估增强的图像质量。绝对色差和特征相似性（FSIM）用于分别测量颜色和灰度图像质量。广泛的实验表明，该方法擅长评估X射线，灰尘，水下和低光图像的增强的图像质量。实验结果与人类主观评价一致，实现了良好的评估效果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号