视觉显著特征融合的图像评价

Image Assessment Based on Feature Pooling of Visual Saliency

针对视觉显著(visual saliency index,VSI)图像质量评价的不足,通过引入人眼的感知特性,提出了一种视觉特征融合(visualsaliencyfeaturepooling,VSFP)的评价方法。VSFP方法首先对失真图像的灰度特征进行评价,作为能量补充信息,然后基于人眼的中央凹生理特性对图像局部特征评价进行加权融合,最后基于回归方程对多特征评价进行自适应融合。实验表明所提方法明显提高了VSI方法的评价性能。

Aiming at the shortcomings of visual saliency index(VSI)for image quality assessment,an assessment method called visual saliency feature pooling(VSFP)is proposed by introducing the perceptual characteristics of human eyes. Firstly,the VSFP method evaluates the gray level features of distorted images are assessed and viewed as energy supplement information. Secondly,the local features assessment is pooled with the weights based on the physiological characteristics of the central foveal of the human eye.Finally,the multi-features assessment is adaptively pooled based on the regression equation. Experiments show that the assessment performance of the proposed method is significantly improved compared to VSI method.