Local and global sparse representation for no-reference quality assessment of stereoscopic images
暂无分享,去创建一个
Mei Yu | Gangyi Jiang | Feng Shao | Fucui Li | Qiuping Jiang | Randi Fu | Mei Yu | G. Jiang | Randi Fu | F. Shao | Fucui Li | Qiuping Jiang
[1] Zhou Wang,et al. No-reference perceptual quality assessment of JPEG compressed images , 2002, Proceedings. International Conference on Image Processing.
[2] Weisi Lin,et al. Perceptual Full-Reference Quality Assessment of Stereoscopic Images by Considering Binocular Visual Characteristics , 2013, IEEE Transactions on Image Processing.
[3] Lei Zhang,et al. Blind Image Quality Assessment Using Joint Statistics of Gradient Magnitude and Laplacian Features , 2014, IEEE Transactions on Image Processing.
[4] David Zhang,et al. FSIM: A Feature Similarity Index for Image Quality Assessment , 2011, IEEE Transactions on Image Processing.
[5] Yuukou Horita,et al. Objective No-Reference Stereoscopic Image Quality Prediction Based on 2D Image Features and Relative Disparity , 2012, Adv. Multim..
[6] Havani,et al. Quality Assessment of Stereoscopic 3 D Image Compression by Binocular Integration Behaviors , 2016 .
[7] G. Nur Yilmaz. A no reference depth perception assessment metric for 3D video , 2015 .
[8] Alan C. Bovik,et al. No-Reference Quality Assessment of Natural Stereopairs , 2013, IEEE Transactions on Image Processing.
[9] Kwanghoon Sohn,et al. No-Reference Quality Assessment for Stereoscopic Images Based on Binocular Quality Perception , 2014, IEEE Transactions on Circuits and Systems for Video Technology.
[10] Damon M. Chandler,et al. 3D-MAD: A Full Reference Stereoscopic Image Quality Estimator Based on Binocular Lightness and Contrast Perception , 2015, IEEE Transactions on Image Processing.
[11] Mohamed-Chaker Larabi,et al. A perceptual metric for stereoscopic image quality assessment based on the binocular energy , 2013, Multidimens. Syst. Signal Process..
[12] S. Hochstein,et al. View from the Top Hierarchies and Reverse Hierarchies in the Visual System , 2002, Neuron.
[13] Lin Ma,et al. Learning structure of stereoscopic image for no-reference quality assessment with convolutional neural network , 2016, Pattern Recognit..
[14] Larry S. Davis,et al. Label Consistent K-SVD: Learning a Discriminative Dictionary for Recognition , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] Matti Pietikäinen,et al. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[16] Asok Ray,et al. Multimodal Task-Driven Dictionary Learning for Image Classification , 2015, IEEE Transactions on Image Processing.
[17] Kwanghyun Lee,et al. 3D Perception Based Quality Pooling: Stereopsis, Binocular Rivalry, and Binocular Suppression , 2015, IEEE Journal of Selected Topics in Signal Processing.
[18] Wenjun Zhang,et al. Using Free Energy Principle For Blind Image Quality Assessment , 2015, IEEE Transactions on Multimedia.
[19] Alan C. Bovik,et al. Subjective evaluation of stereoscopic image quality , 2013, Signal Process. Image Commun..
[20] Alan C. Bovik,et al. No-Reference Image Quality Assessment in the Spatial Domain , 2012, IEEE Transactions on Image Processing.
[21] Xuelong Li,et al. Sparse representation for blind image quality assessment , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[22] Alan C. Bovik,et al. 3D Visual Discomfort Predictor: Analysis of Disparity and Neural Activity Statistics , 2015, IEEE Transactions on Image Processing.
[23] Ashish Kapoor,et al. Blind Image Quality Assessment Using Semi-supervised Rectifier Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[24] Christophe Charrier,et al. Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domain , 2012, IEEE Transactions on Image Processing.
[25] Rama Chellappa,et al. Joint Sparse Representation for Robust Multimodal Biometrics Recognition , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[26] Phong V. Vu,et al. A Fast Wavelet-Based Algorithm for Global and Local Image Sharpness Estimation , 2012, IEEE Signal Processing Letters.
[27] Ja-Ling Wu,et al. Quality Assessment of Stereoscopic 3D Image Compression by Binocular Integration Behaviors , 2014, IEEE Transactions on Image Processing.
[28] Stefan Winkler,et al. A no-reference perceptual blur metric , 2002, Proceedings. International Conference on Image Processing.
[29] Yi Li,et al. Convolutional Neural Networks for No-Reference Image Quality Assessment , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[30] Kai Zeng,et al. Quality Prediction of Asymmetrically Distorted Stereoscopic 3D Images , 2015, IEEE Transactions on Image Processing.
[31] Alan C. Bovik,et al. Making a “Completely Blind” Image Quality Analyzer , 2013, IEEE Signal Processing Letters.
[32] Mei Yu,et al. Supervised dictionary learning for blind image quality assessment , 2015, 2015 Visual Communications and Image Processing (VCIP).
[33] Baihua Li,et al. Quality assessment metric of stereo images considering cyclopean integration and visual saliency , 2016, Inf. Sci..
[34] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[35] Patrick Le Callet,et al. Quality Assessment of Stereoscopic Images , 2008, EURASIP J. Image Video Process..
[36] Lei Zhang,et al. A Feature-Enriched Completely Blind Image Quality Evaluator , 2015, IEEE Transactions on Image Processing.
[37] Alan C. Bovik,et al. Oriented Correlation Models of Distorted Natural Images With Application to Natural Stereopair Quality Evaluation , 2015, IEEE Transactions on Image Processing.
[38] A. Bovik,et al. A universal image quality index , 2002, IEEE Signal Processing Letters.
[39] Alexander Raake,et al. Evaluating Depth Perception of 3D Stereoscopic Videos , 2012, IEEE Journal of Selected Topics in Signal Processing.
[40] Qionghai Dai,et al. Learning Receptive Fields and Quality Lookups for Blind Quality Assessment of Stereoscopic Images , 2016, IEEE Transactions on Cybernetics.
[41] Alan C. Bovik,et al. Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality , 2011, IEEE Transactions on Image Processing.
[42] Do-Kyoung Kwon,et al. Full-reference quality assessment of stereopairs accounting for rivalry , 2013, Signal Process. Image Commun..
[43] Peter Schelkens,et al. Qualinet White Paper on Definitions of Quality of Experience , 2013 .
[44] Wenjun Zhang,et al. No-Reference Stereoscopic IQA Approach: From Nonlinear Effect to Parallax Compensation , 2012, J. Electr. Comput. Eng..
[45] Alan C. Bovik,et al. Image information and visual quality , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[46] Alan C. Bovik,et al. Image information and visual quality , 2006, IEEE Trans. Image Process..
[47] Decebal Constantin Mocanu,et al. Deep learning for objective quality assessment of 3D images , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[48] Qionghai Dai,et al. Full-Reference Quality Assessment of Stereoscopic Images by Learning Binocular Receptive Field Properties , 2015, IEEE Transactions on Image Processing.
[49] Yanqing Li,et al. No-Reference Stereoscopic Image Quality Assessment Using Natural Scene Statistics , 2017, 2017 2nd International Conference on Multimedia and Image Processing (ICMIP).
[50] Lei Zhang,et al. Learning without Human Scores for Blind Image Quality Assessment , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[51] Weisi Lin,et al. On Predicting Visual Comfort of Stereoscopic Images: A Learning to Rank Based Approach , 2016, IEEE Signal Processing Letters.