Opto-Electronic Engineering, Volume. 42, Issue 8, 60(2015)

New Stereo Image Quality Assessment Based on Perception Characteristic Sets and Random Forest

Lü Yaqi*, YU Mei, LIU Shanshan, WANG Ying, and WANG Xiaodong
Author Affiliations
  • [in Chinese]
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    References(13)

    [1] [1] McIntire J P, Havig P R, Geiselman E E. Stereoscopic 3D displays and human performance: a comprehensive review [J]. Displays(S0141-9382), 2014, 35(1): 18-26.

    [3] [3] YOU Junyong, XING Liyuan, Perkis A, et al. Perceptual quality assessment for stereoscopic image based on 2D image quality metrics and disparity analysis [C]// Proc. of International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Scottsdale, AZ, USA, 2010: 4033-4036.

    [4] [4] YANG Jiachen, HOU Chunping, ZHOU Yuan, et al. Objective quality assessment method of stereo images [C]// IEEE 3DTV Conference: The True Vision-Capture, Transmission and Display of 3D Video, Potsdam, Germany, May 4-6, 2009: 1-4.

    [5] [5] Benoit A, Le Callet P, Campisi P, et al. Using disparity for quality assessment of stereoscopic images [C]// Proceedings of the 15th IEEE International Conference on Image Processing(ICIP), San Diego, California, USA, Oct 12-15, 2008: 389-392.

    [6] [6] Hachicha W, Beghdadi A, Cheikh F A. Stereo image quality assessment using a binocular just noticeable difference model[C]// IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, Sept 15-18, 2013: 113-117.

    [9] [9] WANG Zhou, Simoncelli E P, Bovik A C. Multi-scale structural similarity for image quality assessment [C]// Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, Nov 9-12, 2003: 1398-1402.

    [10] [10] Sheikh H R, Bovik A C. Image information and visual quality [J]. IEEE Transactions on Image Processing(S1057-7149), 2006, 15(2): 430-444.

    [11] [11] Shnayderman A, Gusev A, Eskicioglu A M. An SVD-based grayscale image quality measure for local and global assessment [J]. IEEE Transactions on Image Processing(S1057-7149), 2006, 15(2): 422-429.

    [12] [12] Achanta R, Hemami S, Estrada F, et al. Frequency-tuned salient region detection [C]// IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, FL, Jun 20-25, 2009: 1597-1604.

    [13] [13] CHOU Chun-Hsien, LI Yun-Chin. A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile [J]. IEEE Transactions on Circuits and Systems for Video Technology(S1051-8215), 1995, 5(6): 467-476.

    [14] [14] SUN Deqing, Roth S, Black M J. Secrets of optical flow estimation and their principles [C]// IEEE Conference on. Computer Vision and Pattern Recognition(CVPR), San Francisco, CA, Jun 13-18, 2010: 2432-2439.

    [15] [15] Breiman L. Random forests [J]. Machine Learning(S1532-4435), 2001, 45(1): 5-32.

    [16] [16] ZHOU Junming, JIANG Gangyi, MAO Xiangying, et al. Subjective quality analyses of stereoscopic images in 3DTV system [C]// IEEE Visual Communications and Image Processing (VCIP), Tainan, Nov 6-9, 2011: 1-4.

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    Lü Yaqi, YU Mei, LIU Shanshan, WANG Ying, WANG Xiaodong. New Stereo Image Quality Assessment Based on Perception Characteristic Sets and Random Forest[J]. Opto-Electronic Engineering, 2015, 42(8): 60

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    Paper Information

    Category:

    Received: Nov. 3, 2014

    Accepted: --

    Published Online: Sep. 8, 2015

    The Author Email: Yaqi Lü (lvyaqinbu@163.com)

    DOI:10.3969/j.issn.1003-501x.2015.08.010

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