Kanghui Guo

1.9k total citations · 1 hit paper
37 papers, 1.2k citations indexed

About

Kanghui Guo is a scholar working on Applied Mathematics, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Kanghui Guo has authored 37 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Applied Mathematics, 21 papers in Computer Vision and Pattern Recognition and 11 papers in Computational Mechanics. Recurrent topics in Kanghui Guo's work include Image and Signal Denoising Methods (21 papers), Mathematical Analysis and Transform Methods (20 papers) and Advanced Harmonic Analysis Research (10 papers). Kanghui Guo is often cited by papers focused on Image and Signal Denoising Methods (21 papers), Mathematical Analysis and Transform Methods (20 papers) and Advanced Harmonic Analysis Research (10 papers). Kanghui Guo collaborates with scholars based in United States and Canada. Kanghui Guo's co-authors include Demetrio Labate, Guido Weiss, Edward N. Wilson, Wang‐Q Lim, Yibiao Pan, Dashan Fan, Glenn R. Easley, Flavia Colonna, S.W. Drury and Shouchuan Hu and has published in prestigious journals such as Transactions of the American Mathematical Society, Journal of Computational and Applied Mathematics and Proceedings of the American Mathematical Society.

In The Last Decade

Kanghui Guo

36 papers receiving 1.1k citations

Hit Papers

Optimally Sparse Multidimensional Representation Using Sh... 2007 2026 2013 2019 2007 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kanghui Guo United States 14 808 427 399 229 144 37 1.2k
Wang‐Q Lim Germany 11 1.5k 1.9× 1.0k 2.4× 234 0.6× 301 1.3× 160 1.1× 26 1.9k
Glenn R. Easley United States 14 1.2k 1.5× 830 1.9× 194 0.5× 505 2.2× 79 0.5× 48 1.9k
Wayne Lawton Singapore 14 455 0.6× 78 0.2× 350 0.9× 162 0.7× 72 0.5× 45 794
Wenjie He United States 13 849 1.1× 311 0.7× 418 1.0× 231 1.0× 128 0.9× 35 1.1k
Yuli You United States 9 1.2k 1.5× 529 1.2× 50 0.1× 279 1.2× 27 0.2× 19 1.4k
Gabriele Steidl Germany 16 486 0.6× 142 0.3× 59 0.1× 200 0.9× 46 0.3× 36 820
Francine Catté France 4 848 1.0× 236 0.6× 52 0.1× 224 1.0× 38 0.3× 7 1.1k
Matthew Fickus United States 16 314 0.4× 44 0.1× 412 1.0× 254 1.1× 46 0.3× 53 824
Erwan Le Pennec France 11 777 1.0× 426 1.0× 54 0.1× 200 0.9× 40 0.3× 29 992
M.R. Banham United States 8 1.1k 1.3× 556 1.3× 35 0.1× 260 1.1× 25 0.2× 15 1.3k

Countries citing papers authored by Kanghui Guo

Since Specialization
Citations

This map shows the geographic impact of Kanghui Guo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kanghui Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanghui Guo more than expected).

Fields of papers citing papers by Kanghui Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kanghui Guo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kanghui Guo. The network helps show where Kanghui Guo may publish in the future.

Co-authorship network of co-authors of Kanghui Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Kanghui Guo. A scholar is included among the top collaborators of Kanghui Guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kanghui Guo. Kanghui Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Easley, Glenn R., et al.. (2020). Optimally Sparse Representations of Cartoon-Like Cylindrical Data. Journal of Geometric Analysis. 31(9). 8926–8946. 2 indexed citations
2.
Guo, Kanghui, et al.. (2020). Image inpainting using sparse multiscale representations: Image recovery performance guarantees. Applied and Computational Harmonic Analysis. 49(2). 343–380. 1 indexed citations
3.
Guo, Kanghui, et al.. (2018). Directional multiscale representations and applications in digital neuron reconstruction. Journal of Computational and Applied Mathematics. 349. 482–493. 2 indexed citations
4.
Guo, Kanghui & Demetrio Labate. (2017). Detection of Singularities by Discrete Multiscale Directional Representations. Journal of Geometric Analysis. 28(3). 2102–2128. 10 indexed citations
5.
Guo, Kanghui & Demetrio Labate. (2016). Microlocal analysis of edge flatness through directional multiscale representations. Advances in Computational Mathematics. 43(2). 295–318. 3 indexed citations
6.
Guo, Kanghui & Demetrio Labate. (2015). Characterization and analysis of edges in piecewise smooth functions. Applied and Computational Harmonic Analysis. 41(1). 139–163. 7 indexed citations
7.
Guo, Kanghui & Demetrio Labate. (2011). Characterization of Piecewise-Smooth Surfaces Using the 3D Continuous Shearlet Transform. Journal of Fourier Analysis and Applications. 18(3). 488–516. 24 indexed citations
8.
Guo, Kanghui & Demetrio Labate. (2010). Analysis and detection of surface discontinuities using the 3D continuous shearlet transform. Applied and Computational Harmonic Analysis. 30(2). 231–242. 25 indexed citations
9.
Labate, Demetrio & Kanghui Guo. (2010). Optimally sparse 3D approximations using shearlet representations. BearWorks (Missouri State University). 17(0). 125–137. 17 indexed citations
10.
Colonna, Flavia, Glenn R. Easley, Kanghui Guo, & Demetrio Labate. (2009). Radon transform inversion using the shearlet representation. Applied and Computational Harmonic Analysis. 29(2). 232–250. 52 indexed citations
11.
Guo, Kanghui, et al.. (2008). Edge analysis and identification using the continuous shearlet transform. Applied and Computational Harmonic Analysis. 27(1). 24–46. 89 indexed citations
12.
Guo, Kanghui & Demetrio Labate. (2007). Optimally Sparse Multidimensional Representation Using Shearlets. SIAM Journal on Mathematical Analysis. 39(1). 298–318. 467 indexed citations breakdown →
13.
Guo, Kanghui & Demetrio Labate. (2006). Some remarks on the unified characterization of reproducing systems. Collectanea mathematica. 57(3). 295–307. 8 indexed citations
14.
Guo, Kanghui, Demetrio Labate, Wang‐Q Lim, Guido Weiss, & Edward N. Wilson. (2005). Wavelets with composite dilations and their MRA properties. Applied and Computational Harmonic Analysis. 20(2). 202–236. 140 indexed citations
15.
Guo, Kanghui, et al.. (2004). Wavelets with composite dilations. BearWorks (Missouri State University). 10(9). 78–87. 79 indexed citations
16.
Fan, Dashan, Kanghui Guo, & Yibiao Pan. (2002). Lp estimates for singular integrals associated to homogeneous surfaces. Journal für die reine und angewandte Mathematik (Crelles Journal). 2002(542). 1–22. 19 indexed citations
17.
Fan, Dashan, Kanghui Guo, & Yibiao Pan. (1999). A Note of a Rough Singular Integral Operator. Mathematical Inequalities & Applications. 73–81. 24 indexed citations
18.
Guo, Kanghui. (1997). A uniform $L^p$ estimate of Bessel functions and distributions supported on $S^{n-1}$. Proceedings of the American Mathematical Society. 125(5). 1329–1340. 10 indexed citations
19.
Guo, Kanghui. (1994). A Remark on the Spectral Synthesis Property for Hypersurfaces of R n. Proceedings of the American Mathematical Society. 121(1). 185–185. 1 indexed citations
20.
Drury, S.W. & Kanghui Guo. (1991). Convolution estimates related to surfaces of half the ambient dimension. Mathematical Proceedings of the Cambridge Philosophical Society. 110(1). 151–159. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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