• Laser & Optoelectronics Progress
  • Vol. 58, Issue 24, 2410007 (2021)
Mengmeng Ye, Jinbin Hu, Xuejin Wang, and Feng Shao*
Author Affiliations
  • Faculty of Information Science and Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
  • show less
    DOI: 10.3788/LOP202158.2410007 Cite this Article Set citation alerts
    Mengmeng Ye, Jinbin Hu, Xuejin Wang, Feng Shao. No-Reference Stereoscopic Image Quality Assessment Based on Binocular Neuron Response[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2410007 Copy Citation Text show less
    References

    [1] Zhang W, Qu C F, Ma L et al. Learning structure of stereoscopic image for no-reference quality assessment with convolutional neural network[J]. Pattern Recognition, 59, 176-187(2016).

    [2] Moorthy A K, Bovik A C. Blind image quality assessment: from natural scene statistics to perceptual quality[J]. IEEE Transactions on Image Processing, 20, 3350-3364(2011).

    [3] Saad M A, Bovik A C, Charrier C. Blind image quality assessment: a natural scene statistics approach in the DCT domain[J]. IEEE Transactions on Image Processing, 21, 3339-3352(2012).

    [4] Mittal A, Moorthy A K, Bovik A C. No-reference image quality assessment in the spatial domain[J]. IEEE Transactions on Image Processing, 21, 4695-4708(2012).

    [5] He L H, Tao D C, Li X L et al. Sparse representation for blind image quality assessment[C]. //2012 IEEE Conference on Computer Vision and Pattern Recognition, June 16-21, 2012, Providence, RI, USA., 1146-1153(2012).

    [6] Shao F, Li K M, Lin W S et al. Full-reference quality assessment of stereoscopic images by learning binocular receptive field properties[J]. IEEE Transactions on Image Processing, 24, 2971-2983(2015).

    [7] Fu Z Q, Fei Y J, Yang Y et al. No-reference stereoscopic image quality assessment based on deep feature learning[J]. Journal of Optoelectronics·Laser, 29, 545-552(2018).

    [8] Shao F, Lin W S, Gu S B et al. Perceptual full-reference quality assessment of stereoscopic images by considering binocular visual characteristics[J]. IEEE Transactions on Image Processing, 22, 1940-1953(2013).

    [9] Bensalma R, Larabi M C. A perceptual metric for stereoscopic image quality assessment based on the binocular energy[J]. Multidimensional Systems and Signal Processing, 24, 281-316(2013).

    [10] Chen M J, Su C C, Kwon D K et al. Full-reference quality assessment of stereopairs accounting for rivalry[J]. Signal Processing: Image Communication, 28, 1143-1155(2013).

    [11] Huang S Y, Sang Q B. No-reference stereo image quality assessment based on image fusion[J]. Laser & Optoelectronics Progress, 56, 071004(2019).

    [12] Li Y F, Li C F, Sang Q B. No-reference stereo image quality assessment of cyclopean images optimized using quaternion wavelet transform[J]. Laser & Optoelectronics Progress, 56, 181006(2019).

    [13] Su C C, Cormack L K, Bovik A C. Oriented correlation models of distorted natural images with application to natural stereopair quality evaluation[J]. IEEE Transactions on Image Processing, 24, 1685-1699(2015).

    [14] Shao F, Tian W J, Lin W S et al. Toward a blind deep quality evaluator for stereoscopic images based on monocular and binocular interactions[J]. IEEE Transactions on Image Processing, 25, 2059-2074(2016).

    [15] Shao F, Tian W J, Lin W S et al. Learning sparse representation for No-reference quality assessment of multiply distorted stereoscopic images[J]. IEEE Transactions on Multimedia, 19, 1821-1836(2017).

    [16] Shao F, Gao Y, Jiang Q P et al. Multistage pooling for blind quality prediction of asymmetric multiply-distorted stereoscopic images[J]. IEEE Transactions on Multimedia, 20, 2605-2619(2018).

    [17] Ding Y, Zhao Y, Chen X D et al. Stereoscopic image quality assessment by analysing visual hierarchical structures and binocular effects[J]. IET Image Processing, 13, 1608-1615(2019).

    [18] Yang J C, Sim K, Gao X B et al. A blind stereoscopic image quality evaluator with segmented stacked autoencoders considering the whole visual perception route[J]. IEEE Transactions on Image Processing, 28, 1314-1328(2019).

    [19] Kong R, Zhang B. Design of Gabor filters’ parameter[J]. Control and Decision, 27, 1277-1280(2012).

    [20] Shao F, Lin W S, Wang S S et al. Learning receptive fields and quality lookups for blind quality assessment of stereoscopic images[J]. IEEE Transactions on Cybernetics, 46, 730-743(2016).

    [21] Liu Y, Kong F H, Zhen Z Z. Toward a quality predictor for stereoscopic images via analysis of human binocular visual perception[J]. IEEE Access, 7, 69283-69291(2019).

    [22] Wang X J, Qi M L, Shao F et al. Blind quality assessment for multiply distorted stereoscopic images towards IoT-based 3D capture systems[J]. Journal of Visual Communication and Image Representation, 71, 102868(2020).

    [23] Fang Y M, Yan J B, Wang J H et al. Learning a no-reference quality predictor of stereoscopic images by visual binocular properties[J]. IEEE Access, 7, 132649-132661(2019).

    [24] Ohzawa I, DeAngelis G C, Freeman R D. Stereoscopic depth discrimination in the visual cortex: neurons ideally suited as disparity detectors[J]. Science, 249, 1037-1041(1990).

    [25] Read J C, Parker A J, Cumming B G. A simple model accounts for the response of disparity-tuned V1 neurons to anticorrelated images[J]. Visual Neuroscience, 19, 735-753(2002).

    [26] Read J C A, Cumming B G. The psychophysics of stereopsis can be explained without invoking independent ON and OFF channels[J]. Journal of Vision, 19, 7(2019).

    [27] Read J C, Cumming B G. Ocular dominance predicts neither strength nor class of disparity selectivity with random-dot stimuli in primate V1[J]. Journal of Neurophysiology, 91, 1271-1281(2004).

    [28] Moorthy A K, Su C C, Mittal A et al. Subjective evaluation of stereoscopic image quality[J]. Signal Processing: Image Communication, 28, 870-883(2013).

    [29] Chen M J, Cormack L K, Bovik A C. No-reference quality assessment of natural stereopairs[J]. IEEE Transactions on Image Processing, 22, 3379-3391(2013).

    [30] Jiang Q P, Shao F, Gao W et al. Unified no-reference quality assessment of singly and multiply distorted stereoscopic images[J]. IEEE Transactions on Image Processing, 28, 1866-1881(2019).

    Mengmeng Ye, Jinbin Hu, Xuejin Wang, Feng Shao. No-Reference Stereoscopic Image Quality Assessment Based on Binocular Neuron Response[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2410007
    Download Citation