Xiao-Guang Lv

994 total citations
52 papers, 769 citations indexed

About

Xiao-Guang Lv is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Mathematical Physics. According to data from OpenAlex, Xiao-Guang Lv has authored 52 papers receiving a total of 769 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Computer Vision and Pattern Recognition, 25 papers in Computational Mechanics and 12 papers in Mathematical Physics. Recurrent topics in Xiao-Guang Lv's work include Image and Signal Denoising Methods (34 papers), Sparse and Compressive Sensing Techniques (25 papers) and Advanced Image Processing Techniques (19 papers). Xiao-Guang Lv is often cited by papers focused on Image and Signal Denoising Methods (34 papers), Sparse and Compressive Sensing Techniques (25 papers) and Advanced Image Processing Techniques (19 papers). Xiao-Guang Lv collaborates with scholars based in China, United States and Hong Kong. Xiao-Guang Lv's co-authors include Ting‐Zhu Huang, Jun Liu, Le Jiang, Fang Li, Po‐Yu Chen, Ivan Selesnick, Zongben Xu, Jun Liu, Xi-Le Zhao and Si Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Information Sciences.

In The Last Decade

Xiao-Guang Lv

51 papers receiving 743 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiao-Guang Lv China 17 522 314 190 130 73 52 769
Vincent Duval France 11 374 0.7× 368 1.2× 155 0.8× 145 1.1× 51 0.7× 24 735
Tanja Teuber Germany 10 492 0.9× 404 1.3× 146 0.8× 91 0.7× 43 0.6× 17 762
Jungho Yoon South Korea 17 205 0.4× 614 2.0× 94 0.5× 42 0.3× 42 0.6× 70 978
Rüyam Acar Türkiye 6 295 0.6× 253 0.8× 36 0.2× 97 0.7× 62 0.8× 11 626
Triet Le United States 9 463 0.9× 176 0.6× 145 0.8× 71 0.5× 35 0.5× 17 636
Yongli Wang China 13 277 0.5× 210 0.7× 178 0.9× 62 0.5× 52 0.7× 41 549
S. Alliney Italy 11 316 0.6× 190 0.6× 70 0.4× 40 0.3× 50 0.7× 35 554
Joachim Stöckler Germany 15 481 0.9× 439 1.4× 34 0.2× 19 0.1× 67 0.9× 33 926
Tuomo Valkonen Finland 9 170 0.3× 196 0.6× 29 0.2× 35 0.3× 70 1.0× 39 413
Abdelilah Hakim Morocco 15 461 0.9× 148 0.5× 206 1.1× 35 0.3× 39 0.5× 71 650

Countries citing papers authored by Xiao-Guang Lv

Since Specialization
Citations

This map shows the geographic impact of Xiao-Guang Lv'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 Xiao-Guang Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiao-Guang Lv more than expected).

Fields of papers citing papers by Xiao-Guang Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao-Guang Lv. 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 Xiao-Guang Lv. The network helps show where Xiao-Guang Lv may publish in the future.

Co-authorship network of co-authors of Xiao-Guang Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Xiao-Guang Lv. A scholar is included among the top collaborators of Xiao-Guang Lv 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 Xiao-Guang Lv. Xiao-Guang Lv 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.
Mei, Jiaqi, et al.. (2024). Contrast-preserving image smoothing via the truncated first-order rational function. Signal Processing. 227. 109700–109700. 1 indexed citations
2.
Lv, Xiao-Guang, et al.. (2023). Fast additive half‐quadratic iterative minimization for l p l q image smoothing. IET Image Processing. 17(6). 1739–1751. 3 indexed citations
3.
Lv, Xiao-Guang, et al.. (2022). Nonconvex variational approach for simultaneously recovering cartoon and texture images. Journal of Electronic Imaging. 31(4). 2 indexed citations
4.
Liu, Jun, et al.. (2021). Poisson noisy image restoration via overlapping group sparse and nonconvex second-order total variation priors. PLoS ONE. 16(4). e0250260–e0250260. 3 indexed citations
5.
Yang, Changqing, et al.. (2020). Jacobi spectral collocation method for solving fractional pantograph delay differential equations. Engineering With Computers. 38(3). 1985–1994. 16 indexed citations
6.
Lv, Xiao-Guang, Fang Li, & Tieyong Zeng. (2018). Convex blind image deconvolution with inverse filtering. Inverse Problems. 34(3). 35003–35003. 7 indexed citations
7.
Liu, Jun, Ting‐Zhu Huang, Xiao-Guang Lv, & Si Wang. (2017). High-order total variation-based Poissonian image deconvolution with spatially adapted regularization parameter. Applied Mathematical Modelling. 45. 516–529. 23 indexed citations
8.
Li, Fang & Xiao-Guang Lv. (2017). A Decoupled method for image inpainting with patch-based low rank regulariztion. Applied Mathematics and Computation. 314. 334–348. 4 indexed citations
9.
Huang, Ting‐Zhu, et al.. (2015). Restoration of blurred color images with impulse noise. Computers & Mathematics with Applications. 70(6). 1255–1265. 17 indexed citations
10.
Xu, Yi, Ting‐Zhu Huang, Jun Liu, & Xiao-Guang Lv. (2014). An augmented Lagrangian algorithm for total bounded variation regularization based image deblurring. Journal of the Franklin Institute. 351(6). 3053–3067. 6 indexed citations
11.
Lv, Xiao-Guang, et al.. (2014). The comparisons of two special Hermitian and skew-Hermitian splitting methods for image restoration. Applied Mathematical Modelling. 39(3-4). 1275–1280. 3 indexed citations
12.
Lv, Xiao-Guang & Ting‐Zhu Huang. (2013). The Inverses of Block Toeplitz Matrices. SHILAP Revista de lepidopterología. 2013. 1–8. 7 indexed citations
13.
Lv, Xiao-Guang, et al.. (2013). Image restoration with a high-order total variation minimization method. Applied Mathematical Modelling. 37(16-17). 8210–8224. 70 indexed citations
14.
Wang, Si, Ting‐Zhu Huang, Jun Liu, & Xiao-Guang Lv. (2013). An alternating iterative algorithm for image deblurring and denoising problems. Communications in Nonlinear Science and Numerical Simulation. 19(3). 617–626. 15 indexed citations
15.
Liu, Jun, Ting‐Zhu Huang, Zongben Xu, & Xiao-Guang Lv. (2013). High-order total variation-based multiplicative noise removal with spatially adapted parameter selection. Journal of the Optical Society of America A. 30(10). 1956–1956. 21 indexed citations
16.
Zhao, Xi-Le, Ting‐Zhu Huang, Xiao-Guang Lv, Zongben Xu, & Jie Huang. (2011). Kronecker product approximations for image restoration with new mean boundary conditions. Applied Mathematical Modelling. 36(1). 225–237. 8 indexed citations
17.
Jiang, Le, et al.. (2010). A PRECONDITIONED METHOD FOR THE SOLUTION OF THE ROBBINS PROBLEM FOR THE HELMHOLTZ EQUATION. The ANZIAM Journal. 52(1). 87–100. 16 indexed citations
18.
Lv, Xiao-Guang, Ting‐Zhu Huang, & Zhigang Ren. (2009). A modified T. Chan’s preconditioner for Toeplitz systems. Computers & Mathematics with Applications. 58(4). 693–699. 4 indexed citations
19.
Lv, Xiao-Guang, Ting‐Zhu Huang, & Zhigang Ren. (2008). A new algorithm for linear systems of the Pascal type. Journal of Computational and Applied Mathematics. 225(1). 309–315. 6 indexed citations
20.
Lv, Xiao-Guang & Le Jiang. (2008). A note on solving nearly penta-diagonal linear systems. Applied Mathematics and Computation. 204(2). 707–712. 11 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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