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Journal

  • Y. Zhang, Q. Yang, D. M. Chandler, and X. Mou, “Reference-based multi-stage progressive restoration for multi-degraded images,” IEEE Transactions on Image Processing, vol. 33, 2024. PDF

  • Q. Yang, Y. Zhang, D. M. Chandler, and M. C. Farias, “SSRT: Intra- and cross-view attention for stereo image super-resolution,” Multimedia Tools and  Applications, (2024): 1-29. PDF

  • Y. Zhang, D. M. Chandler, and M. Leszczuk, “Retinex-based underwater image enhancement via adaptive color correction and hierarchical U-shape transformer,” Optics Express, vol. 32, no. 14, July 2024. PDF

  • Y. Zhang, D. M. Chandler, and X. Mou, “Deep neural network based distortion parameter estimation for blind quality measurement of stereoscopic images,” Signal Processing: Image Communication, 126 (2024), 117138. PDF

  • Y. Zhang, D. M. Chandler, and X. Mou, “Deep steerable pyramid wavelet network for unified JPEG compression artifact reduction,” Signal Processing: Image Communication, 118 (2023), 117011. PDF

  • Y. Zhang, D. M. Chandler, and X. Mou, “Multi-domain residual encoder–decoder networks for generalized compression artifact reduction,” Journal of Visual Communication and Image Representation, vol. 83, February 2022, 103425. PDF

  • Y. Zhang, D. M. Chandler, and X. Mou, “Quality assessment of multiply and singly distorted stereoscopic images via adaptive construction of cyclopean views,” Signal Processing: Image Communication, 94 (2021), 116175. PDF

  • Y. Zhang, X. Mou, and D. M. Chandler, “Learning No-Reference Quality Assessment of Multiply and Singly Distorted Images with Big Data,” IEEE Transactions on Image Processing, vol. 29, no. 1, pp. 2676~2691, December 2020.  PDF

  • R. Liu, Q. Miao, Y. Zhang, M. Gong, and P. Xu, “A Semi-Supervised High-Level Feature Selection Framework for Road Centerline Extraction,” IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 5, May, 2020. PDF

  • Y. Zhang, D. M. Chandler, “Opinion-Unaware Blind Quality Assessment of Multiply and Singly Distorted Images via Distortion Parameter Estimation,” IEEE Transactions on Image Processing, vol. 27, no. 11, November 2018. PDF

  • Y. Zhang, D. M. Chandler, and X. Mou, “Quality Assessment of Screen Content Images via Convolutional-Neural-Network-Based Synthetic/Natural Segmentation,” IEEE Transactions on Image Processing, vol. 27, no. 10, November 2018. PDF

  • J. Holloway, V. Kannan, Y. Zhang, D. M. Chandler, and S. Sohoni, “GPU Acceleration of the Most Apparent Distortion Image Quality Assessment Algorithm,” Journal of Imaging, 4(10), 2018. PDF

  • R. S. Allison, K. Brunnström, D. M. Chandler, H. R. Colett, P. J. Corriveau, S. Daly, J. Goel, J. Y. Long; L. M. Wilcox, Y. M. Yaacob, S. Yang, and Y. Zhang, “Perspectives on the definition of visually lossless quality for mobile and large format displays,” Journal of Electronic Imaging, 27(05): 053035-1~053035-23, 2018. PDF

  • Y. Zhang, T. D. Phan, and D. M. Chandler, “Reduced reference image quality assessment based on distortion families of local perceived sharpness”, Signal Processing: Image Communication, 55(2017) 130-145. PDF

  • Y. Zhang, D. M. Chandler, “3D-MAD: A full reference stereoscopic image quality estimator based on binocular lightness and contrast perception,” IEEE Transactions on Image Processing, vol. 24, no. 11, November 2015. PDF

  • Y. Zhang, A. K. Moorthy, D. M. Chandler, and A. C. Bovik, “C-DIIVINE: No-Reference Imagel  Quality Assessment Based on Local Magnitude and Phase Statistics of Natural Scenes,” Signal Processing: Image Communication, 29(7), August 2014. PDF

  • Y. Zhang, D. M. Chandler, “No-reference image quality assessment based on log-derivative statistics of natural scenes,” Journal of Electronic Imaging, 22(4), 043025, 2013. PDF

  • 张君昌, 张译, 基于自适应权重更新和遗传算法的人脸检测, 西北工业大学学报, 29(2), 2011. 

  • 张君昌, 张译, 基于改进AdaBoost算法的人脸检测，计算机仿真, 28(7), 2011.

Conference

  • R. Liu, Y. Zhang, D. M. Chandler, Q. Miao, and T. Liu, “LaG-DESIQUE: A Local-and-Global Blind Image Quality Evaluator Without Training on Human Opinion Scores”, 6th CCF Academic Conference on Big Data, Xi'an, Oct. 11-13, 2018.

  • J. Tang, P. Xu, W. Nie, Y. Zhang, and R. Liu, “A Review of Recent Advances in Identity Identification Technology Based on Biological Features”, 6th CCF Academic Conference on Big Data, Xi'an, Oct. 11-13, 2018.

  • Y. Zhang, D. M. Chandler, “Learning natural statistics of binocular contrast for no reference quality assessment of stereoscopic image”, International Conference on Image Processing, Beijing, Sep. 17-20, 2017. PDF

  • Y. Zhang, Y. M. Yaacob, and D. M. Chandler, “Masked detection of compression artifacts on laboratory, consumer, and mobile displays (Invited),” IS&T Conference of Human Vision and Electronic Imaging, CA, USA, 2017. 

  • Y. M. Yaacob, Y. Zhang, and D. M. Chandler, “On the perceptual factors underlying the quality of post-compression enhancement of textures,” IS&T Conference of Human Vision and Electronic Imaging, CA, USA, 2017. PDF

  • Y. Zhang, D. M. Chandler, “An algorithm for no-reference image quality assessment based on log-derivative statistics of natural scene,” SPIE Conference on Image Quality and System Performance, Burlingame, CA, USA, February 2013. PDF

  • J. Zhang, Y. Zhang, and Z. Ye, “Adaptive Speech Enhancement Based on Classification of Voiced/Unvoiced Signal”, International Conference on Multimedia and Signal Processing (CMSP), vol. 2, pp. 310-314, Guilin, May 2011. 

  • J. Zhang, Y. Zhang, “Human Face Detection Based on Genetic Algorithm”, The 2nd International Conference on Information Science and Engineering, vol.10, Hangzhou, December 2010.

Book Chapter

  • Y. Zhang, M. M. Alam, and D. M. Chandler, “Visually lossless perceptual image coding based on natural-scene masking models,” Chapter 1 of the book Recent Advance in Image and Video Coding, IntechOpen, DOI: 10.5772/65362, 2016. 

Patent

  • 张译，禹冬晔，牟轩沁，“一种无参考立体混合失真图像质量评价方法”，ZL202011097823.2

  • 张译，禹冬晔，牟轩沁，“一种基于可控金字塔小波网络的JPEG图像压缩伪影消除方法”，ZL202111155935.3

  • 张译，禹冬晔，牟轩沁，“一种基于级联残差编解码网络的JPEG图像压缩伪影消除算法”，ZL202011530001.9