失焦图像的无参考质量评价  

Blind quality assessment for the out-of-focus blurred images

作　　者：刘玉涛 赵德斌[1] LIU Yutao;ZHAO Debin(School of Computer Science and Technology,Harbin Institute of Technology,Harbin 150001,China)

机构地区：[1]哈尔滨工业大学计算机科学技术学院,哈尔滨150001

出　　处：《智能计算机与应用》2018年第5期1-7,12,共8页Intelligent Computer and Applications

基　　金：国家973项目(KMQQ2480124217)

摘　　要：自然图像很容易受到不同失真的干扰,比如模糊、噪声、块效应等,这些失真都会降低图像的质量。在所有失真图像里面,失焦图像是最常见的失真图像,而且占据了很大的比例。然而,针对失焦图像质量评价的研究仍然较少。因此,在这篇文章中,提出了一个专门的失焦图像质量评价的方法,叫做GPSQ。在GPSQ中,首先提取2种低视觉层次的特征,包括梯度幅值(Gradient Magnitude)和相位一致性(Phase Congruency)来度量图像的模糊度;然后,对失焦图像进行显著性检测,从而得到图像的显著图。最后,利用图像的显著图加权图像的结构图而对图像的视觉质量做出估计。实验结果证明了本文提出的方法 GPSQ取得了与主观质量评价较高的一致性。Images are vulnerable to different kinds of distortions,such as blur,noise,blocking,etc.,which all degrade the image quality. Among the distorted images,out-of-focus blurred images are frequently-encountered and occupy a large proportion.However,fewefforts have been done to quality evaluation for these images. In this paper,a dedicated quality evaluation scheme is devised to automatically infer the quality of out-of-focus blurred images,which is named GPSQ（ Gradient magnitude and Phase congruency-based and Saliency-guided Quality model）. In GPSQ,a pair of low-level features,including Gradient Magnitude（ GM） and Phase Congruency（ PC）,are extracted to characterize the image local blurriness. Then saliency detection is performed on the image to generate a corresponding saliency map. Finally,the local structure map with the saliency map is weighted to estimate the visual quality of the out-of-focus blurred image. Experimental results demonstrate the proposed GPSQ delivers high consistency with subjective evaluation results.

关 键 词：视觉质量评价 失焦模糊 相位一致性 图像显著性 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]