利用相位一致性的图像质量评价方法

摘要

各种图像处理建立在有效性地提取图像特征之上，如图像分类、分割和图像质量评价等，因此获取有效的图像特征对于图像处理意义十分重大。不同于在图像灰度的突变点处直接定义图像特征，相位一致性（PC）在傅里叶分量的相位保持高度一致的位置观测图像特征，获得了丰富的特征信息和精确的特征定位，与人类视觉系统（HVS）对图像特征的认知相符。提出了一种新的基于相位一致性特征的图像质量评价方法。该方法使用退化与参考图像的相位一致性在局部区域的相似度来测量图像质量的退化程度；并且考虑到相位一致性是纹理和边缘的反应，而人类视觉系统对纹理丰富的区域较为敏感，利用相位一致的局部最值作为加权值，将局部的相似度结合为单个的图像质量评分值。实验结果表明，提出的图像质量指标具有较好的主客观一致性。尤为重要的是，该指标对图像的亮度和对比度变化不敏感。%In practical image processing, some post-processing operations largely depend on the availability of image fea-tures. Operations, like classification, segmentation, and image quality assessment, are often carried out in a feature space. The availability of image features plays an important role for further analysis. Rather than defining features directly at points with sharp change in intensity, the Phase Congruency(PC), which is a dimensionless measure of the significant of a local structure, postulates that features are perceived at points where the Fourier components are maximal in phase. The PC model is in accordance with the human visual system that demonstrates good invariance to light conditions and can achieve effective feature information and well feature location accuracy. Based on those properties, it proposes a new image quality metric based on the PC model, which utilizes the local similarities of phase congruency between the reference and distorted image to quantify the image distortion. Moreover, considering that human visual system is sensitive to phase con-gruent structures and that the PC value at a location can reflect how likely it is a perceptibly significant structure point, PC values at a location are employed to combine the similarities within local regions into a single quality score. The experi-mental result shows that the proposed algorithm is correlated well with the judgment of human observers. More importantly, the metric is invariant to changes in image brightness or contrast.