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SWVFS： a saliency weighted visual feature similarity metric for image quality assessment

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Frontiers of Computer Science 2014年第1期8卷 145-155页

作者： Li CUI School of Electronics and Information Northwestern Polytechnical University Xi'an 710072 China

In this paper, a saliency weighted visual feature similarity （SWVFS） metric is proposed for full reference im- age quality assessment （IQA）. Instead of traditional spatial pooling strategies, a visual saliency-based approach is em- ployed for better compliance with properties of the human visual system, where the saliency allocation is closely related to the activity of posterior parietal cortex and the pluvial nu- clei of the thalamus. Assuming that the saliency map actually represents the contribution of locally computed visual distor- tions to the overall image quality, the gradient similarity and the textural congruency are merged into the final image qual- ity indicator. The gradient and texture comparison play com- plementary roles in characterizing the local image distortion. Extensive experiments conducted on seven publicly available image databases show that the performance of SWVFS is competitive with the state-of-the-art IQA algorithms.

关键词： image quality assessment gradient texture vi-sual saliency

image Signature Based Mean Square Error for image quality assessment

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Chinese Journal of Electronics 2015年第4期24卷 755-760页

作者： CUI Ziguan GAN Zongliang TANG Guijin LIU Feng ZHU Xiuchang image Processing and image Communication Laboratory Nanjing University of Posts and Telecommunications

Motivated by the importance of Human visual system(HVS) in image processing, we propose a novel image signature based mean square error(ISMSE)metric for full reference image quality assessment(IQA).Efficient image signature based describer is used to predict visual saliency map of the reference image. The saliency map is incorporated into luminance difference between the reference and distorted images to obtain image quality score. The effect of luminance difference on visual quality with larger saliency value which is usually corresponding to foreground objects is highlighted. Experimental results on LIVE database release 2 show that by integrating the effects of image signature based saliency on luminance difference, the proposed ISMSE metric outperforms several state-of-the-art HVS-based IQA metrics but with lower complexity.

关键词： image quality assessment Human visual system image signature Saliency Mean square error

A Novel Spatial Pooling Strategy for image quality assessment

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Journal of Computer Science & Technology 2016年第2期31卷 225-234页

作者： Qiaohong Li Yu-Ming Fang Member, CCF Jing-Tao Xu School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore School of Information Technology Jiangxi University of Finance and Economics Nanchang 330013 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100086 China

A variety of existing image quality assessment （IQA） metrics share a similar two-stage framework： at the first stage, a quality map is constructed by comparison between local regions of reference and distorted images; at the second stage, the spatial pooling is adopted to obtain overall quality score. In this work, we propose a novel spatial pooling strategy for image quality assessment through statistical analysis of the quality map. Our in-depth analysis indicates that the overall image quality is sensitive to the quality distribution. Based on the analysis, the quality histogram and statistical descriptors extracted from the quality map are used as input to the support vector regression to obtain the final objective quality score. Experimental results on three large public IQA databases have demonstrated that the proposed spatial pooling strategy can greatly improve the quality prediction performance of the original IQA metrics in terms of correlation with human subjective ratings.

关键词： image quality assessment spatial pooling statistical pooling support vector regression structural similarity

Bridge the Gap Between Full-Reference and No-Reference:A Totally Full-Reference Induced Blind image quality assessment via Deep Neural Networks

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China Communications 2023年第6期20卷 215-228页

作者： Xiaoyu Ma Suiyu Zhang Chang Liu Dingguo Yu Communication University of Zhejiang No.998Xueyuan RoadQiantang DistrictHangzhou 310042ZhejiangChina Peng Cheng Laboratory No.2Xingke RoadNanshan DistrictShenzhen 518055GuangdongChina

Blind image quality assessment(BIQA)is of fundamental importance in low-level computer vision *** interest has been drawn in exploiting deep neural networks for *** of the notable success achieved,there is a broad consensus that training deep convolutional neural networks(DCNN)heavily relies on massive annotated ***,BIQA is typically a small sample problem,resulting the generalization ability of BIQA severely *** order to improve the accuracy and generalization ability of BIQA metrics,this work proposed a totally opinion-unaware BIQA in which no subjective annotations are involved in the training *** full-reference image quality assessment(FR-IQA)metrics are employed to label the distorted image as a substitution of subjective quality annotation.A deep neural network(DNN)is trained to blindly predict the multiple FR-IQA score in absence of corresponding pristine *** the end,a selfsupervised FR-IQA score aggregator implemented by adversarial auto-encoder pools the predictions of multiple FR-IQA scores into the final quality predicting *** though none of subjective scores are involved in the training stage,experimental results indicate that our proposed full reference induced BIQA framework is as competitive as state-of-the-art BIQA metrics.

关键词： deep neural networks image quality assessment adversarial auto encoder

image quality assessment method based on nonlinear feature extraction in kernel space

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Frontiers of Information Technology & Electronic Engineering 2016年第10期17卷 1008-1017页

作者： Yong DING Nan LI Yang ZHAO Kai HUANG Institute of VLSI Design Zhejiang University Hangzhou 310027 China

To match human perception, extracting perceptual features effectively plays an important role in image quality assessment. In contrast to most existing methods that use linear transformations or models to represent images, we employ a complex mathematical expression of high dimensionality to reveal the statistical characteristics of the images. Furthermore, by introducing kernel methods to transform the linear problem into a nonlinear one, a full-reference image quality assessment method is proposed based on high-dimensional nonlinear feature extraction. Experiments on the LIVE, TID2008, and CSIQ databases demonstrate that nonlinear features offer competitive performance for image inherent quality representation and the proposed method achieves a promising performance that is consistent with human subjective evaluation.

关键词： image quality assessment Full-reference method Feature extraction Kernel space Support vector regression

Perceptual image quality assessment metric using mutual information of Gabor features

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Science China(Information Sciences) 2014年第3期57卷 130-138页

作者： DING Yong ZHANG Yuan WANG Xiang YAN XiaoLang KRYLOV Andrey S. Institute of VLSI Design Zhejiang University Laboratory of Mathematical Methods of image Processing Lomonosov Moscow State University

A good objective metric of image quality assessment(IQA)should be consistent with the subjective judgment of human *** this paper,a four-stage perceptual approach for full reference IQA is *** the first stage,the visual features are extracted by 2-D Gabor filter that has the excellent performance of modeling the receptive fields of simple cells in the primary visual *** in the second stage,the extracted features are post-processed by the divisive normalization transform to reflect the nonlinear mechanisms in human visual *** the third stage,mutual information between the visual features of the reference and distorted images is employed to measure the visual *** in the last pooling stage,the mutual information is converted to the final objective quality *** results show that the proposed metic has a high correlation with the subjective assessment and outperforms other state-of-the-art metrics.

关键词： image quality assessment mutual information Gabor features perceptual metric entropy

Color image quality assessment Based on Structural Similarity

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Journal of Donghua University(English Edition) 2010年第4期27卷 443-450页

作者：卢芳芳赵群飞杨根科 Department of Automation Shanghai Jiaotong University

It is well-known that classical quality measures,such as Mean Squared Error(MSE),Weighted Mean Squared Error(WMSE)or Peak Signal-to-Noise Ratio(PSNR),are not always corresponding with visual *** similarity based image quality assessment was proposed under the assumption that the Human Visual System(HVS)is highly adapted for extracting structural information from an *** the demand on high color quality increases in the media industry,color loss will make the visual quality *** this paper,we proposed an improved quality assessment(QA)method by adding color comparison into the structural similarity(SSIM)measurement system for evaluating color image *** we divided the task of similarity measurement into four comparisons:luminance,contrast,structure,and *** results show that the predicted quality scores of the proposed method are more effective and consistent with visual quality than the classical methods using five different distortion types of color image sets.

关键词： image quality assessment structural similarity difference mean opinion score color image

Blind image quality assessment Based on Hybrid Fuzzy-Genetic Technique

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Journal of Beijing Institute of Technology 2003年第4期12卷 395-398页

作者：王海沈庭芝谢志宏 Department of Electronic Engineering

A new method for no-reference image quality assessment based on hybrid fuzzy-genetic technique is proposed. Noise variance and edge sharpness level of the restored image are two basic metrics for assessing the performance of the restoration algorithm, then a fuzzy if-then inference system is developed to combine the two metrics to get a final quality score, and the parameters of the fuzzy membership function are trained with genetic algorithms. Experiments results show that the image quality score correlates well with mean opinion score and the proposed approach is robust and effective.

关键词： image quality assessment fuzzy inference system genetic algorithms

A METHOD OF image quality assessment FOR COMPRESSIVE SAMPLING VIDEO TRANSMISSION

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Journal of Electronics(China) 2012年第6期29卷 598-603页

作者： Chen Shouning Zheng Baoyu Li Jing Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications

Based on compressive sampling transmission model, we demonstrate here a method of quality evaluation for the reconstruction images, which is promising for the transmission of unstructured signal with reduced dimension. By this method, the auxiliary information of the recovery image quality is obtained as a feedback to control number of measurements from compressive sampling video stream. Therefore, the number of measurements can be easily derived at the condition of the absence of information sparsity, and the recovery image quality is effectively improved. Theoretical and experimental results show that this algorithm can estimate the quality of images effectively and is in well consistency with the traditional objective evaluation algorithm.

关键词： Compressive sampling image quality assessment Measurements feedback