Matan Protter

5.6k total citations · 2 hit papers
9 papers, 1.5k citations indexed

About

Matan Protter is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Media Technology. According to data from OpenAlex, Matan Protter has authored 9 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 4 papers in Computational Mechanics and 2 papers in Media Technology. Recurrent topics in Matan Protter's work include Image and Signal Denoising Methods (6 papers), Sparse and Compressive Sensing Techniques (4 papers) and Advanced Image Processing Techniques (4 papers). Matan Protter is often cited by papers focused on Image and Signal Denoising Methods (6 papers), Sparse and Compressive Sensing Techniques (4 papers) and Advanced Image Processing Techniques (4 papers). Matan Protter collaborates with scholars based in Israel, United States and Cayman Islands. Matan Protter's co-authors include Michael Elad, Peyman Milanfar, Hiroyuki Takeda, Lihi Zelnik‐Manor, Itamar Friedman, Emanuel Ben-Baruch, Asaf Noy, Tal Ridnik, Yaniv Romano and Irad Yavneh and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

In The Last Decade

Matan Protter

9 papers receiving 1.4k citations

Hit Papers

Generalizing the Nonlocal-Means to Super-Resolution Recon... 2008 2026 2014 2020 2008 2021 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matan Protter Israel 7 1.2k 527 221 220 97 9 1.5k
Florian Luisier Switzerland 13 1.3k 1.2× 729 1.4× 275 1.2× 157 0.7× 131 1.4× 28 1.8k
Daniel Zoran United States 11 1.3k 1.1× 748 1.4× 236 1.1× 144 0.7× 44 0.5× 18 1.5k
Yuhui Quan China 27 1.7k 1.4× 717 1.4× 281 1.3× 231 1.1× 96 1.0× 88 2.1k
Christian J. Schuler Germany 10 1.5k 1.3× 963 1.8× 144 0.7× 198 0.9× 72 0.7× 11 2.0k
Shai Bagon Israel 10 1.6k 1.4× 745 1.4× 120 0.5× 100 0.5× 69 0.7× 17 1.9k
Yacov Hel-Or Israel 19 973 0.8× 331 0.6× 138 0.6× 162 0.7× 39 0.4× 55 1.3k
Daniel Gläsner United States 10 1.6k 1.3× 848 1.6× 86 0.4× 168 0.8× 67 0.7× 17 1.8k
Yaniv Romano Israel 13 818 0.7× 343 0.7× 336 1.5× 107 0.5× 155 1.6× 23 1.2k
Dacheng Tao China 14 1.7k 1.5× 830 1.6× 209 0.9× 381 1.7× 42 0.4× 18 2.1k
M.J. Black United States 13 1.5k 1.3× 411 0.8× 186 0.8× 193 0.9× 52 0.5× 16 1.8k

Countries citing papers authored by Matan Protter

Since Specialization
Citations

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

Fields of papers citing papers by Matan Protter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matan Protter. 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 Matan Protter. The network helps show where Matan Protter may publish in the future.

Co-authorship network of co-authors of Matan Protter

This figure shows the co-authorship network connecting the top 25 collaborators of Matan Protter. A scholar is included among the top collaborators of Matan Protter 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 Matan Protter. Matan Protter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Ridnik, Tal, Emanuel Ben-Baruch, Asaf Noy, et al.. (2021). Asymmetric Loss For Multi-Label Classification. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 82–91. 323 indexed citations breakdown →
2.
Ben-Cohen, Avi, et al.. (2019). Attention Network Robustification for Person ReID. 4 indexed citations
3.
Romano, Yaniv, Matan Protter, & Michael Elad. (2014). Single Image Interpolation Via Adaptive Nonlocal Sparsity-Based Modeling. IEEE Transactions on Image Processing. 23(7). 3085–3098. 89 indexed citations
4.
Protter, Matan, Irad Yavneh, & Michael Elad. (2010). Closed-Form MMSE Estimation for Signal Denoising Under Sparse Representation Modeling Over a Unitary Dictionary. IEEE Transactions on Signal Processing. 58(7). 3471–3484. 57 indexed citations
5.
Takeda, Hiroyuki, Peyman Milanfar, Matan Protter, & Michael Elad. (2009). Super-Resolution Without Explicit Subpixel Motion Estimation. IEEE Transactions on Image Processing. 18(9). 1958–1975. 215 indexed citations
6.
Protter, Matan, Michael Elad, Hiroyuki Takeda, & Peyman Milanfar. (2008). Generalizing the Nonlocal-Means to Super-Resolution Reconstruction. IEEE Transactions on Image Processing. 18(1). 36–51. 507 indexed citations breakdown →
7.
Protter, Matan & Michael Elad. (2008). Image Sequence Denoising via Sparse and Redundant Representations. IEEE Transactions on Image Processing. 18(1). 27–35. 246 indexed citations
8.
Protter, Matan, Irad Yavneh, & Michael Elad. (2008). Closed-form mmse estimator for denoising signals under sparse representation modelling. 580–584. 2 indexed citations
9.
Protter, Matan & Michael Elad. (2007). Sparse and redundant representations and motion-estimation-free algorithm for video denoising. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6701. 67011D–67011D. 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026