关键词: 特征提取, 相位一致性, 边缘检测, 图像质量评价

Abstract: In practical image processing, some post-processing operations largely depend on the availability of image features. 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 congruent 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 experimental 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.

Key words: feature extraction, phase congruency, edge detection, image quality assessment