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NEW VISUAL PERCEPTUAL POOLING STRATEGY FOR IMAGE QUALITY ASSESSMENT 被引量:2

NEW VISUAL PERCEPTUAL POOLING STRATEGY FOR IMAGE QUALITY ASSESSMENT
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摘要 Most of Image Quality Assessment (IQA) metrics consist of two processes. In the first process, quality map of image is measured locally. In the second process, the last quality score is converted from the quality map by using the pooling strategy. The first process had been made effective and significant progresses, while the second process was always done in simple ways. In the second process of the pooling strategy, the optimal perceptual pooling weights should be determined and computed according to Human Visual System (HVS). Thus, a reliable spatial pooling mathematical model based on HVS is an important issue worthy of study. In this paper, a new Visual Perceptual Pooling Strategy (VPPS) for IQA is presented based on contrast sensitivity and luminance sensitivity of HVS. Experimental results with the LIVE database show that the visual perceptual weights, obtained by the proposed pooling strategy, can effectively and significantly improve the performances of the IQA metrics with Mean Structural SIMilarity (MSSIM) or Phase Quantization Code (PQC). It is confirmed that the proposed VPPS demonstrates promising results for improving the performances of existing IQA metrics. Most of Image Quality Assessment (IQA) process, quality map of image is measured locally. In metrics consist of two processes. In the first the second process, the last quality score is converted from the quality map by using the pooling strategy. The first process had been made effective and significant progresses, while the second process was always done in simple ways. In the second process of the pooling strategy, the optimal perceptual pooling weights should be determined and computed according to Human Visual System (HVS). Thus, a reliable spatial pooling mathematical model based on HVS is an important issue worthy of study. In this paper, a new Visual Perceptual Pooling Strategy (VPPS) for IQA is presented based on contrast sensitivity and luminance sensitivity of HVS. Experimental results with the LIVE database show that the visual perceptual weights, obtained by the proposed pooling strategy, can effectively and significantly improve the performances of the IQA metrics with Mean Structural SIMilarity (MSSIM) or Phase Quantization Code (PQC). It is confirmed that the proposed VPPS demonstrates promising results for improving the performances of existing IQA metrics.
出处 《Journal of Electronics(China)》 2012年第3期254-261,共8页 电子科学学刊(英文版)
基金 Supported by the National Natural Science Foundation of China (No. 60832003, 60902096, 61171163, 61071120) the Scientific Research Foundation of Graduate School of Ningbo University
关键词 Image Quality Assessment (IQA) Visual Perceptual Pooling Strategy(VPPS) Contrast Sensitivity Function (CSF) Luminance Sensitivity Function (LSF) Image Quality Assessment (IQA) Visual Perceptual Pooling Strategy(VPPS) Contrast Sensitivity Function (CSF) Luminance Sensitivity Function (LSF)
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  • 1A.A.Panayides,M.S.Pattichis,C.S.Pattichis. Atherosclerotic plaque ultrasound video encoding,wireless transmission,and quality assessment using H.264[J].IEEE Transactions on Information Technology in Biomedicine,2011,(03):387-397.
  • 2G.Cheng,L.Cheng. Geometric directional distortion for full reference image quality assessment[J].Electronics Letters,2009,(25):1305-1307.
  • 3C.Y.Wee,R.Paramesran,R,Mukundan. Image quality assessment by discrete orthogonal moments[J].Pattern Recognition,2010,(12):4055-4068.
  • 4F.Zhang,L.Ma,S.N.Li. Practical image quality metric applied to image coding[J].IEEE Transactions on Multimedia,2011,(04):615-624.
  • 5Q.Huynh-Thu,M.Ghanbari. Scope of validity of PSNR in image/video quality assessment[J].Electronics Letters,2008,(13):800-801.
  • 6Z.Wang,A.C.Bovik. Mean squared error:Love it or leave it? A new look at Signal Fidelity Measures[J].IEEE Signal Processing Magazine,2009,(01):98-117.
  • 7C.Bovik,R.S.Hamid. Image quality assessment:from error visibility to structural similarity[J].IEEE Transactions on Image Processing,2004,(04):600-612.
  • 8Dong-O Kim,Rae-Hong Park. Image quality measure using the phase quantization code[J].IEEE Transactions on Consumer Electronics,2010,(02):937-945.
  • 9C.F.Li,A.C.Bovik. Content-partitioned structural similarity index for image quality assessment[J].Signal Processing:Image Communication,2010,(07):517-526.
  • 10A.K.Moorthy,A.C.Bovik. Visual importance pooling for image quality assessment[J].IEEE Journal of Selected Topics in Signal Processing,2009,(02):193-201.

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