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  • Phd Thesis:

 

    • "Etudes de modeles variationnels et apprentissage de dictionnaires", Universite Paris Nord. Oct.2007, PDF.

 

  • Publications:

 

 

 

 

    • L. Ma, L. Xu, and T. Zeng, "Low rank prior and total variation regularization for image deblurring'', Journal of Scientific Computing, vol. 70, no. 3, pp 1336-1357, 2017.

 

    • F. Fang, F. Li and T. Zeng, "Reducing Spatially Varying Out-of-Focus Blur from Natural Image'', Inverse Problems and Imaging, vol. 11, no. 1, pp.65-85, 2017. PDF.

 

 

 

 

 

 

 

 

 

 

    • R. Abergel, C. Louchet, L. Moisan, and T. Zeng, "Total Variation Restoration of Images Corrupted by Poisson Noise with Iterated Conditional Expectations''. Scale Space and Variational Methods in Computer Vision, LNCS 9087, pp 178-190, 2015. PDF.

 

 

    • H. Chang, M. Ng, W. Wang, T. Zeng, "Retinex Image Enhancement via a Learned Dictionary", Optical Engineering, vol. 54, no.1, 013107, 2015.

 

 

 

 

 

 

 

    • Y. Peng, S. Ying, J. Qin and T. Zeng, "Trimmed strategy for affine registration of point sets", Journal of Applied Remote Sensing, vol. 7, no. 1, 2013.

 

 

    • F. Li, and T. Zeng, "Image Restoration via Tight Frame Regularization and Local Constraints". Journal of Scientific Computing, vol. 57, no. 2, pp. 349-371, November 2013. PDF.

 

 

 

    • L. Ma, J. Yu, and T. Zeng, " Sparse Representation Prior and Total Variation--Based Image Deblurring Under Impulse Noise". SIAM Journal on Imaging Sciences, vol. 6, no. 4. pp. 2258-2284, 2013. PDF.

 

 

 

 

 

 

 

    • X. Cai, R. Chan, and T. Zeng, "A Two-stage Image Segmentation Method using a Convex Variant of the Mumford-Shah Model and Thresholding". SIAM Journal on Imaging Sciences, vol. 6, no. 1, pp. 368-390, 2013. PDF.

 

 

 

 

 

 

    • Y. Xiao, T. Zeng, J. Yu and M. Ng, "Restoration of Images Corrupted by Mixed Gaussian-Impulse Noise via l_1-l_0 Minimization". Pattern Recognition, vol. 44, no. 8, pp. 1708-1728, August 2011.

 

    • L. Jing, T. Zeng and M. Ng, "On Gene Selection and Classification for Cancer Microarray Data Using Multi-step Clustering and Sparse Representation". Advances in Adaptive Data Analysis, vol. 3, no. 1-2 (2011), pp. 127-148.

 

 

 

 

    • Y. Xiao, T. Zeng, "Poisson noise removal via learned dictionary", Proceedings of IEEE ICIP'10, pp. 1177-1180, September 26-29, 2010, Hong Kong.

 

    • K. Cai, X. Li, T. Zeng, B. Yang, X. Lu, "Reliable histogram features for detecting LSB matching", Proceedings of IEEE ICIP'10, pp. 1761-1764, September 26-29, 2010, Hong Kong.

 

    • Y. Gao, X. Li, T. Zeng, B. Yang, "Improving embedding efficiency via matrix embedding: a case study", Proceedings of IEEE ICIP'09, pp. 109-112, November 7-11, 2009, Cairo, Egypt.

 

 

 

    • X. Li, T. Zeng, B.Yang, " A Further Study on Steganalysis of LSB Matching by Calibration", Proceedings of IEEE ICIP'08, pp. 2072-2075, October 12-15, 2008. San Diego, California, U.S.A. PDF.

 

    • T. Zeng, "Incorporating known features into a total variation dictionary model for source separation", Proceedings of IEEE ICIP'08, pp. 577-580, October 12-15, 2008. San Diego, California, U.S.A. PDF.

 

    • X. Li, T. Zeng, B.Yang, "Detecting LSB Matching by Applying Calibration Technique for Difference Image", Proceedings of the 10th ACM Multimedia and Security Workshop (ACM MM&SEC 2008, pp.133-138, September22-23, 2008, Oxford, UK. PDF.

 

    • X. Li, T. Zeng, B.Yang, "Improvement of the Embedding Efficiency of LSB Matching by Sum and Difference Covering Set", Proceedings of IEEE ICME'08, pp. 209-212, Hannover, Germany, June 23-26, 2008. PDF

 

    • T. Zeng, F. Malgouyres, "Using Gabor dictionaries in a $TV-l^\infty$ model, for denoising", Proceedings of ICASSP 2006, vol. 2, pp. 865-868, Toulouse, France, May 14-19, 2006. PDF.