王凡, 倪晋平, 董涛, 郭荣礼. 结合视觉注意力机制和图像锐度的无参图像质量评价方法[J]. 应用光学, 2018, 39(1): 51-56. DOI: 10.5768/JAO201839.0101009
引用本文: 王凡, 倪晋平, 董涛, 郭荣礼. 结合视觉注意力机制和图像锐度的无参图像质量评价方法[J]. 应用光学, 2018, 39(1): 51-56. DOI: 10.5768/JAO201839.0101009
Wang Fan, Ni Jinping, Dong Tao, Guo Rongli. No-reference image quality assessment method based on visual attention mechanism and sharpness metric approach[J]. Journal of Applied Optics, 2018, 39(1): 51-56. DOI: 10.5768/JAO201839.0101009
Citation: Wang Fan, Ni Jinping, Dong Tao, Guo Rongli. No-reference image quality assessment method based on visual attention mechanism and sharpness metric approach[J]. Journal of Applied Optics, 2018, 39(1): 51-56. DOI: 10.5768/JAO201839.0101009

结合视觉注意力机制和图像锐度的无参图像质量评价方法

No-reference image quality assessment method based on visual attention mechanism and sharpness metric approach

  • 摘要: 针对模糊图像的质量评价,提出一种新的无参图像质量评价方法,该方法结合了自底向上的视觉注意力机制和自顶向下的图像锐度评价标准。根据人眼视觉注意力机制模型,分别计算颜色、亮度和方向显著度图像,通过竞争机制得到人眼优先关注的区域; 利用无参图像锐度评价方法分别对优先关注的区域及背景区域进行评价,综合2个区域的评价结果得到最终的图像质量评价指标。利用该方法分别对相向运动过程中所产生的模糊图像和图像质量评价Live数据库中的高斯模糊图像进行了评价,结果表明:针对两类图像的评价结果与主观评价结果的相关系数均较高,其中,针对相向运动模糊图像的主客观评价结果的相关系数达到0.98。该方法能够胜任对模糊图像的客观质量评价。

     

    Abstract: A no-reference image quality assessment method based on bottom-up visual attention mechanism and top-down image sharpness metric is proposed for the blur image quality evaluation.Firstly, the color, intensity and orientation feature maps are calculated based on the human visual attention mechanism, and then the saliency region of the image is obtained by the winner-take-all competition. Secondly, the image of saliency region and the background region are evaluated using no-reference image sharpness evaluation method, and the final image quality index can be obtained by the combination of the above two results.The radial blur images produced in the forward motion imaging and the Gauss fuzzy images in the Live database evaluation are evaluated using the proposed method respectively.Experiment results can prove that the correlation coefficient between the results of our method and the subjective one is larger than 0.98 for the radial blur images.The method can be used for evaluating the blur image subjectively.

     

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