Wang‐Q Lim

3.2k total citations · 2 hit papers
26 papers, 1.9k citations indexed

About

Wang‐Q Lim is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing. According to data from OpenAlex, Wang‐Q Lim has authored 26 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 8 papers in Media Technology and 7 papers in Signal Processing. Recurrent topics in Wang‐Q Lim's work include Image and Signal Denoising Methods (17 papers), Advanced Image Fusion Techniques (8 papers) and Video Coding and Compression Technologies (7 papers). Wang‐Q Lim is often cited by papers focused on Image and Signal Denoising Methods (17 papers), Advanced Image Fusion Techniques (8 papers) and Video Coding and Compression Technologies (7 papers). Wang‐Q Lim collaborates with scholars based in Germany, United States and Thailand. Wang‐Q Lim's co-authors include Demetrio Labate, Glenn R. Easley, Gitta Kutyniok, Guido Weiss, Kanghui Guo, Edward N. Wilson, Heiko Schwarz, Thomas Wiegand, Detlev Marpe and Gabriele Steidl and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology and Progress of Theoretical Physics.

In The Last Decade

Wang‐Q Lim

23 papers receiving 1.8k citations

Hit Papers

Sparse directional image representations using the discre... 2007 2026 2013 2019 2007 2010 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wang‐Q Lim Germany 11 1.5k 1.0k 301 234 195 26 1.9k
Nick Kingsbury United Kingdom 14 1.8k 1.2× 850 0.8× 285 0.9× 171 0.7× 220 1.1× 46 2.5k
Glenn R. Easley United States 14 1.2k 0.8× 830 0.8× 505 1.7× 194 0.8× 407 2.1× 48 1.9k
Vasily Strela United States 14 2.4k 1.6× 1.4k 1.4× 370 1.2× 240 1.0× 137 0.7× 15 2.7k
Kanghui Guo United States 14 808 0.5× 427 0.4× 229 0.8× 399 1.7× 74 0.4× 37 1.2k
N. Kingsbury United Kingdom 25 1.9k 1.3× 656 0.7× 235 0.8× 112 0.5× 135 0.7× 81 2.4k
Jean–François Aujol France 26 1.9k 1.2× 629 0.6× 736 2.4× 50 0.2× 178 0.9× 81 2.4k
Bradley J. Lucier United States 18 1.1k 0.7× 322 0.3× 597 2.0× 300 1.3× 169 0.9× 44 1.9k
Leonid Yaroslavsky Israel 19 1.2k 0.8× 696 0.7× 179 0.6× 49 0.2× 160 0.8× 92 1.8k
Hyeokho Choi United States 19 1.0k 0.7× 476 0.5× 160 0.5× 79 0.3× 87 0.4× 53 1.3k
Tomeu Coll Spain 3 1.8k 1.2× 389 0.4× 382 1.3× 51 0.2× 157 0.8× 3 2.3k

Countries citing papers authored by Wang‐Q Lim

Since Specialization
Citations

This map shows the geographic impact of Wang‐Q Lim'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 Wang‐Q Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wang‐Q Lim more than expected).

Fields of papers citing papers by Wang‐Q Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wang‐Q Lim. 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 Wang‐Q Lim. The network helps show where Wang‐Q Lim may publish in the future.

Co-authorship network of co-authors of Wang‐Q Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Wang‐Q Lim. A scholar is included among the top collaborators of Wang‐Q Lim 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 Wang‐Q Lim. Wang‐Q Lim 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.
Lim, Wang‐Q, et al.. (2022). Performance-Complexity Analysis of Adaptive Loop Filter with a CNN-based Classification. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 91–95. 1 indexed citations
2.
Pfaff, Jonathan, Heiko Schwarz, Detlev Marpe, et al.. (2019). Video Compression Using Generalized Binary Partitioning, Trellis Coded Quantization, Perceptually Optimized Encoding, and Advanced Prediction and Transform Coding. IEEE Transactions on Circuits and Systems for Video Technology. 30(5). 1281–1295. 23 indexed citations
3.
Lim, Wang‐Q, Heiko Schwarz, Detlev Marpe, & Thomas Wiegand. (2019). Post Sample Adaptive Offset for Video Coding. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 1–5. 2 indexed citations
4.
Dahmen, Wolfgang, Gitta Kutyniok, Wang‐Q Lim, Christoph Schwab, & Gerrit Welper. (2018). Adaptive anisotropic Petrov–Galerkin methods for first order transport equations. Journal of Computational and Applied Mathematics. 340. 191–220.
5.
Lim, Wang‐Q, et al.. (2018). Shearlet-based Loop Filter. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 141–145.
6.
Lim, Wang‐Q, et al.. (2018). Multiple Feature-based Classifications Adaptive Loop Filter. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 91–95. 5 indexed citations
7.
Kutyniok, Gitta & Wang‐Q Lim. (2016). Dualizable Shearlet Frames and Sparse Approximation. Constructive Approximation. 44(1). 53–86. 1 indexed citations
8.
Reisenhofer, Rafael, et al.. (2015). Shearlet-based edge detection: flame fronts and tidal flats. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9599. 959905–959905. 9 indexed citations
9.
Lim, Wang‐Q. (2013). Nonseparable Shearlet Transform. IEEE Transactions on Image Processing. 22(5). 2056–2065. 74 indexed citations
10.
Kutyniok, Gitta, et al.. (2013). Image inpainting: theoretical analysis and comparison of algorithms. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8858. 885802–885802. 6 indexed citations
11.
Kutyniok, Gitta & Wang‐Q Lim. (2011). Image Separation Using Shearlets. arXiv (Cornell University). 10 indexed citations
12.
Kutyniok, Gitta & Wang‐Q Lim. (2011). Compactly supported shearlets are optimally sparse. Journal of Approximation Theory. 163(11). 1564–1589. 111 indexed citations
13.
Lim, Wang‐Q. (2011). Discrete shearlet transform: faithful digitization concept and its applications. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8138. 813810–813810.
14.
Kutyniok, Gitta, et al.. (2011). Construction of Compactly Supported Shearlet Frames. Constructive Approximation. 35(1). 21–72. 66 indexed citations
15.
Lim, Wang‐Q. (2010). The Discrete Shearlet Transform: A New Directional Transform and Compactly Supported Shearlet Frames. IEEE Transactions on Image Processing. 19(5). 1166–1180. 325 indexed citations breakdown →
16.
Easley, Glenn R., Demetrio Labate, & Wang‐Q Lim. (2007). Sparse directional image representations using the discrete shearlet transform. Applied and Computational Harmonic Analysis. 25(1). 25–46. 793 indexed citations breakdown →
17.
Easley, Glenn R., Demetrio Labate, & Wang‐Q Lim. (2006). Optimally Sparse Image Representations using Shearlets. 5. 974–978. 37 indexed citations
18.
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
19.
Labate, Demetrio, Wang‐Q Lim, Gitta Kutyniok, & Guido Weiss. (2005). Sparse multidimensional representation using shearlets. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5914. 59140U–59140U. 293 indexed citations
20.
Lim, Wang‐Q, et al.. (2001). New Riddling Bifurcation in Asymmetric Dynamical Systems. Progress of Theoretical Physics. 105(2). 187–196. 4 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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