To further explore the human visual system（ HVS）,the perceptual grouping（ PG）, which has been proven to play an important role in the HVS, is adopted to design an effective image quality assessment（ IQA） model. ...To further explore the human visual system（ HVS）,the perceptual grouping（ PG）, which has been proven to play an important role in the HVS, is adopted to design an effective image quality assessment（ IQA） model. Compared with the existing fixed-window-based models, the proposed one is an adaptive window-like model that introduces the perceptual grouping strategy into the IQA model. It works as follows： first,it preprocesses the images by clustering similar pixels into a group to the greatest extent; then the structural similarity is used to compute the similarity of the superpixels between reference and distorted images; finally, it integrates all the similarity of superpixels of an image to yield a quality score. Experimental results on three databases（ LIVE, IVC and MICT） showthat the proposed method yields good performance in terms of correlation with human judgments of visual quality.展开更多
Constant levels of perceptual quality of streaming video is what ideall usersexpect. In most cases, however, they receive time-varying levels of quality of video. In thispaper, the author proposes a new control method...Constant levels of perceptual quality of streaming video is what ideall usersexpect. In most cases, however, they receive time-varying levels of quality of video. In thispaper, the author proposes a new control method of perceptual quality in variable bit rate videoencoding for streaming video. The image quality calculation based on the perception of human visualsystems is presented . Quantization properties of DCT coefficients are analyzed to controleffectively. Quantization scale factors are ascertained based on the visual mask effect. AProportional Integral Difference (PID) controller is used to control the image quality. Experimentalresults show that this method improves the perceptual quality uniformity of encoded video.展开更多
A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation(DNSGA-II)strategy is proposed to make the product appearance optimization ...A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation(DNSGA-II)strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product.First,the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users;then,the product multidimensional scale analysis is applied to classify the research objects,and again the reference samples are screened by the semantic differentialmethod,and the samples are parametrized in two dimensions by using elliptic Fourier analysis;finally,the fuzzy dynamic evaluation function is used as the objective function of the algorithm,and the coordinates of key points of product contours Finally,with the fuzzy dynamic evaluation function as the objective function of the algorithm and the coordinates of key points of the product profile as the decision variables,the optimal product profile solution set is solved by DNSGA-II.The validity of the model is verified by taking the optimization of the shape scheme of the hospital connection site as an example.For comparison with DNSGA-II,other multi-objective optimization algorithms are also presented.To evaluate the performance of each algorithm,the performance evaluation index values of the five multi-objective optimization algorithms are calculated in this paper.The results show that DNSGA-II is superior in improving individual diversity and has better overall performance.展开更多
基金The National Natural Science Foundation of China(No.81272501)the National Basic Research Program of China(973Program)(No.2011CB707904)Taishan Scholars Program of Shandong Province,China(No.ts20120505)
文摘To further explore the human visual system（ HVS）,the perceptual grouping（ PG）, which has been proven to play an important role in the HVS, is adopted to design an effective image quality assessment（ IQA） model. Compared with the existing fixed-window-based models, the proposed one is an adaptive window-like model that introduces the perceptual grouping strategy into the IQA model. It works as follows： first,it preprocesses the images by clustering similar pixels into a group to the greatest extent; then the structural similarity is used to compute the similarity of the superpixels between reference and distorted images; finally, it integrates all the similarity of superpixels of an image to yield a quality score. Experimental results on three databases（ LIVE, IVC and MICT） showthat the proposed method yields good performance in terms of correlation with human judgments of visual quality.
文摘Constant levels of perceptual quality of streaming video is what ideall usersexpect. In most cases, however, they receive time-varying levels of quality of video. In thispaper, the author proposes a new control method of perceptual quality in variable bit rate videoencoding for streaming video. The image quality calculation based on the perception of human visualsystems is presented . Quantization properties of DCT coefficients are analyzed to controleffectively. Quantization scale factors are ascertained based on the visual mask effect. AProportional Integral Difference (PID) controller is used to control the image quality. Experimentalresults show that this method improves the perceptual quality uniformity of encoded video.
基金supported by National Natural Science Foundation Grant 52065010the Science and Technology Project supported by Guizhou Province of China ZK[2021]341 and[2021]397the transformation Project of Scientific and Technological Achievements in Guiyang,Guizhou Province,China[2021]7-3.
文摘A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation(DNSGA-II)strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product.First,the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users;then,the product multidimensional scale analysis is applied to classify the research objects,and again the reference samples are screened by the semantic differentialmethod,and the samples are parametrized in two dimensions by using elliptic Fourier analysis;finally,the fuzzy dynamic evaluation function is used as the objective function of the algorithm,and the coordinates of key points of product contours Finally,with the fuzzy dynamic evaluation function as the objective function of the algorithm and the coordinates of key points of the product profile as the decision variables,the optimal product profile solution set is solved by DNSGA-II.The validity of the model is verified by taking the optimization of the shape scheme of the hospital connection site as an example.For comparison with DNSGA-II,other multi-objective optimization algorithms are also presented.To evaluate the performance of each algorithm,the performance evaluation index values of the five multi-objective optimization algorithms are calculated in this paper.The results show that DNSGA-II is superior in improving individual diversity and has better overall performance.
