Submitted

• Yuchen He, Sung-Ha Kang, Wenjing Liao, Hao Liu and Yingjie Liu, "Group projected Subspace Pursuit for Identification of variable coefficient differential equations (GP-IDENT)", arXiv:2304.05543, submitted 2023
• Yuchen He, Sung Ha Kang, and Jean-Michel Morel, "A variational image vectorization algorithm on Dual-Primal graph pairs", submitted 2023
• Yuchen He, Sung Ha Kang, and Jean-Michel Morel, "Topology and perception aware image vectorization", submitted 2022
• Yaghoub Rahimi, Sung Ha Kang and Yifei Lou, "A lifted l1 framework for sparse recovery", arxiv:2203.05125, submitted

Recent publications

• Martin Huska, Antonio Cicone, Sung Ha Kang, and Serena Morigi, ``A two-stage signal decomposition into Jump, Oscillation and Trend using ADMM", IPOL 2023.
• Ho Mark Law, Guangyu Cui, and Sung Ha Kang, ``Surface Reconstruction from 2D Noisy Point Cloud Data using Directional G-norm", 9th Internationalnal Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 2023.
• Mengyi Tang, Wenjing Liao, Rachel Kuske, and Sung Ha Kang, ``WeakIdent: Weak formulation for Identifying Differential Equations using Narrow-fit and Trimming", Journal of Computational Physics, Volume 483, 15, June 2023, Github link for code, 2023 (arxiv:2211.03134)
• Mengyi Tang, Kumbit Hwang and Sung Ha Kang, "StemP: A fast and deterministic Stem-graph approach for RNA folding prediction", IEEE/ACM Transactions on Computational Biology and Bioinformatics, Github link for codes, 2023 (arXiv:2201.05724)
• Benjamin McLaughlin and Sung Ha Kang, "A new parallel adaptive clustering and its application to streaming data", Journal of Computational Science, Volume 66, January 2023 (arXiv:2104.02680),
• Yuchen He, Sung Ha Kang, Jean-Michel Morel, "Vectorizing images of any size", 2022 IEEE International Conference on Image Processing (ICIP), October 2022
• Mengyi Tang, Maryam Yashtini and Sung Ha Kang, "Counting Objects by Diffused Index: geometry-free and training-free approach", Journal of Visual Communication and Image Representation, Volume 86, July 2022 (arXiv:2110.08365)
• Yuchen He, Namjoon Suh, Xiaoming Huo, Sung-Ha Kang, and Yajun Mei, "Asymptotic Theory l1-Regularized PDE Identification from a Single Noisy Trajectory", SIAM ASA Journal on Uncertainty Quantification, Vol. 10, Iss. 3, 2022 (arXiv:2103.07045)
• Antonio Cicone, Martin Huska, Sung-Ha Kang and Serena Morigi, ``JOT: a Variational Signal Decomposition into Jump, Oscillation and Trend", IEEE Transactions on Signal Processing, 70, 772-784, 2022.
• Yuchen He, Sung-Ha Kang, Wenjing Liao, Hao Liu and Yingjie Liu, ``Numerical Identification of Nonlocal Potentials in Aggregation", Communications in Computational Physics, 32, pp. 638 -- 670, 2022. (arXiv:2207.03358)
• Yuchen He, Sung-Ha Kang, Wenjing Liao, Hao Liu and Yingjie Liu, ``Robust Identification of Differential Equations by Numerical Techniques from a single set of noisy observation (Robust IDENT from a single set of noisy observation)", SIAM Journal on Scientific Computing, 44(3), 2022 (arXiv:2006.06557).
• Yuchen He, Sung Ha Kang, Jean-Michel Morel, ``Silhouette Vectorization by Affine Scale-space", Journal of Mathematical Imaging and Vision, 64, 41-56, 2022, (arXiv:2007.12117).
• Martin Huska, Sung Ha Kang, Alessandro Lanza, and Serena Morigi, ``A Variational Approach to Additive Image Decomposition into Structure, Harmonic and Oscillatory Components", SIAM Journal on Imaging Sciences, 14 (4), 2021.
• Yuchen He, Sung Ha Kang, Jean-Michel Morel, ``Accurate Silhouette Vectorization by Affine Scale-Space", 2021 IEEE International Conference on Image Processing (ICIP), Septermber 19-22, 2021.
• Yuchen He, Sung Ha Kang, Luis Alvarez, ``Finding the skeleton of 2D shape and contours: implementation of Hamilton-Jacobi Skeleton", Image Processing On Line, 11 (2021), pp. 18 -- 36. https://doi.org/10.5201/ipol.2021.296
• Sung Ha Kang, Wenjing Liao, and Yingjie Liu, ``IDENT: Identifying Differential Equations with Numerical Time evolution", Journal of Scientific Computing, 87, 1, 2021, (ArXiv:1904.03538).
• Yuchen He, Sung Ha Kang, and Hao Liu, ``Curvature Regularized Surface Reconstruction from Point Cloud", SIAM Journal on Imaging Sciences13(4), 1834-1859 (2020), (ArXiv:2001.07884).
• Yuchen He, Martin Huska, Sung Ha Kang, and Hao Liu, ``Fast Algorithms for Surface Reconstruction from Point Cloud", In the proceedings of the International Workshop on Image Processing and Inverse Problems (IPIP 2018) (Springer) Pages 61-80, 2021. (ArXiv: 1907.01142)
• Sung Ha Kang, Xuecheng Tai and Wei Zhu, ``Survey of geometry inspired variational segmentation: interface model, curvature terms and fast computation ", Handbook of Numerical Analysis, Elsevier, Volume 20, 2019.
• Yuchen (Roy) He, and Sung Ha Kang, ``Lattice Identication and Separation: Theory and Algorithm" (LISA), SIAM Journal on Imaging Sciences, 12(4), 2063 -- 2096, 2019 (ArXiv:1901.02520).
• Yuchen (Roy) He, and Sung Ha Kang, ``Lattice Metric Space Application to Grain Defect Detection", the proceedings of the 7th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 2019.
• Maryam Yashtini, Sung Ha Kang, and Wei Zhu, ``Efficient Alternating Minimization Methods For Variational Edge-weighted Colorization Models", Advances in Computational Mathematics, 45, pages 1735 -- 1767, 2019
• Sung Ha Kang, Seong Jun Kim, and Haomin Zhou, ``Optimal Sensor Positioning (OSP); A Probability Perspective Study", SIAM Journal on Scientific Computing , 39(5), 759 -- 777, 2017
• Xiong Ding and Sung Ha Kang, ``Stepsize-adaptive integrators for dissipative solitons in cubic-quintic complex Ginzburg-Landau equations", 20217 (ArXiv:1703.09622)

2008- 2016

• Maryam Yashtini and Sung Ha Kang, ``A fast relaxed normal two split method and an effective weighted TV approach for Euler's elastica image inpainting", SIAM Journal of Imaging Science , Volume 9, Number 4, pages 1552-1581, 2016.
• Maryam Yashtini, Sung Ha Kang, ``Alternating Direction Method of Multiplier for Euler's Elastica-Based Denoising", International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 690-701, 2015.
• Sung Ha Kang, Seong Jun Kim, and Haomin Zhou, ``Path optimization with limited sensing ability", Journal of Computational Physics , Volume 299, 15, pages 887–901, October 2015 (UCLA CAM 14-99)
• Sung Ha Kang, Wei Zhu, and Jianhong (Jackie) Shen, ``Illusory Shapes via Corner Fusion", SIAM Journal on Imaging Sciences, 7(4), 1907–1936, 2014 (UCLA CAM 14-21)
• Sung Ha Kang and Riccardo March, ``Multiphase image segmentation via equally distanced multiple well potential", Journal of Visual Communication and Image Representation , Volume 25, Issue 6, Pages 1446 -- 1459, 2014.
• Sung Ha Kang, Behrang Shafei and Gabriele Steidl, ``Supervised and Transductive Multi-Class Segmentation Using p-Laplacians and RKHS Method", Journal of Visual Communication and Image Representation, Volume 25, Issue 5, Pages 1136 -- 1148, July 2014.
• Guozhi Dong, Markus Grasmair, Sung Ha Kang, and Otmar Scherzer, ``Scale and Edge Detection with Topological Derivatives", Fourth International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) June 2013.
• Yifei Lou, Sung Ha Kang, Stefano Soatto and Andrea Bertozzi, ``Video Stabilization of Atmospheric Turbulence Distortion", Inverse Problems and Imaging , Pages: 839 - 861, Volume 7, Issue 3, 2013. (UCLA CAM 12-30)
• Wei Zhu, Sung Ha Kang and George Biros, ``A geodesic active contour based variational model for short axis cardiac-MR image segmentation", International Journal of Computer Mathematics , Volume 90, Issue 1,124-139, 2013
• Sung Ha Kang and Riccardo March, ``Existence and regularity of minimizers of a functional for unsupervised multiphase segmentation", Nonlinear Analysis Series A: Theory, Methods & Applications, Volume 76, Pages 181 -- 201, January 2013.
• Sung Ha Kang, Berta Sandberg and Andy Yip, ``A Regularized K-means and Multiphase Scale Segmentation", Inverse problems and imaging, Volume 5, Issue 2, Pages 407-429, 2011 (UCLA CAM 10-53)
• Frank Crosby and Sung Ha Kang, ``Multiphase Segmentation for 3D Flash Lidar Images", Journal of Pattern Recognition Research, Vol 6, No 2, 193-200, 2011
• Minh Ha-Quang, Sung-Ha Kang, and Triet M. Le, ``Image and Video Colorization Using Vector-Valued Reproducing Kernel Hilbert Spaces", Journal of Mathematical Imaging and Vision , Volume 37, Number 1, Pages: 49 - 65, 2010. (UCLA CAM 09-46)
• Berta Sandberg, Sung Ha Kang, and Tony F. Chan, ``Unsupervised Multiphase Segmentation: A phase balancing model", IEEE transaction in Image Processing, Volume: 19, Issue: 1, pages: 119 - 130, 2010. ( UCLA CAM 08-02)
• Marco Barchiesi, Sung Ha Kang, Triet Le, Massimiliano Morini, Marcello Ponsiglione, ``A variational model for infinite perimeter segmentations based on Lipschitz level set functions: denoising while keeping finely oscillatory boundaries", SIAM Multiscale Modeling and Simulation , Volume 8, Issue 5, pp. 1715-1741, 2010
• Triet Le, Minh Ha-Quang and Sung-Ha Kang, ``Reproducing kernel and colorization", Proceedings of the 8th International Conference on Sampling Theory and Applications (SAMPTA 09), May 2009.

2000 to 2008

• Tony. F. Chan, Sung Ha Kang and Jianhong Shen, ``Total variation denoising and enhancement of color images based on the CB and HSV color Models'', Journal of Visual Communication and Image Representation, Volume 12, Issue 4, Pages 422-435, 2001. Full color images available at: UCLA CAM00-25.
• Tony. F. Chan, Sung Ha Kang and Jianhong Shen,``Euler's Elastica and curvature based inpaintings'', SIAM journal on Applied Mathematics, Volume 63, Number 2, Pages 564-592, 2002. Preprint UCLA CAM01-12 .
• Sung Ha Kang, Tony. F. Chan and Stefano Soatto, ``Inpainting from Multiple view", IEEE Proceedings of First International Symposium on 3D Data Processing Visualization Transmission, Pages 622-625, 2002. Preprint UCLA CAM 02-31.
• Sung Ha Kang and Jianhong Shen, "Video dejittering by bake and shake", Image and vision computing, Volume 24, Issue 2, Pages 143-152, 2006. Full color images available at: UCLA CAM 04-60.
• Tony F. Chan and Sung Ha Kang, ``Error analysis for image inpainting'', Journal of Mathematical Imaging and Vision, Volume 26, Number 1-2, pages 85-103, 2006. Full color images available at: UCLA CAM 04-72.
• Jean-Francois Aujol and Sung Ha Kang, ''Color image decomposition and restoration'', Journal of Visual Communication and Image Representation , Volume 17, Issue 4, pages 916-928, 2006. Full color images available at: UCLA CAM04-73.
• Sung Ha Kang and Jianhong Shen, ``On the slicing moments of BV functions and applications to image dejittering'', Image Processing Based on Partial Differential Equations, Springer-Verlag, Berlin, pages 35-55, 2007. Preprint UCLA CAM05-11.
• Sung Ha Kang and Riccardo March, ``Variational models for image colorization via Chromaticity and Brightness decomposition'', IEEE transaction in Image Processing, Volume 16, Issue 9, Pages 2251-2261, 2007. Full color images : IMA preprint 2138.
• Yoon Mo Jung, Sung Ha Kang and Jianhong Shen, ``Multiphase image segmentation via Modica-Mortola phase transition'', SIAM applied Mathematics, Volume 67, Issue 5, Pages 1213- 1232, 2007. Preprint UCLA CAM06-31, IMA preprint 2124
• Jianhong Shen and Sung Ha Kang, ``Quantum TV and Applications in Image Processing'', Inverse Problems and Imaging, Volume 1, Number 3, Pages 557-575, 2007. Preprint UCLA CAM07-09.
• James H. Money and Sung Ha Kang, ``Total variation semi-blind deconvolution using shock filters", Image and Vision Computing Volume 26, Issue 2, Pages 302-314, 2008.

Technical Reports

• Jeff Anderson, Feng-Nan Hwang, Sung Ha Kang, Bahareh Momken, Richard Shugart, Caroline Torcaso, ``Modeling molecular diffusion in soft tissues using fluorescence microscopy", NCSU tech report CRSC-TR00-24, 2000.
• Sung Ha Kang, Tony F. Chan and Stefano Soatto, ``Landmark based inpainting from Multiple view", UCLA Math CAM Report 02-11, March 2002.
• SeongJai Kim and Sung Ha Kang, ``Implicit Procedures for PDE-based Color Images Denoising via Brightness-Chromaticity", UK tech report 02-07, 2002.