F. Salzenstein

837 total citations
29 papers, 591 citations indexed

About

F. Salzenstein is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Media Technology. According to data from OpenAlex, F. Salzenstein has authored 29 papers receiving a total of 591 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 9 papers in Computational Mechanics and 7 papers in Media Technology. Recurrent topics in F. Salzenstein's work include Image and Signal Denoising Methods (8 papers), Optical measurement and interference techniques (7 papers) and Surface Roughness and Optical Measurements (6 papers). F. Salzenstein is often cited by papers focused on Image and Signal Denoising Methods (8 papers), Optical measurement and interference techniques (7 papers) and Surface Roughness and Optical Measurements (6 papers). F. Salzenstein collaborates with scholars based in France, Canada and United Kingdom. F. Salzenstein's co-authors include Abdel‐Ouahab Boudraa, C. Collet, Wojciech Pieczynski, Paul Montgomery, Jean-Christophe Cexus, Mathieu Hatt, Akram Belghith, Catherine Cheze‐Le Rest, Christian Roux and Dimitris Visvikis and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Optics Express and Physics in Medicine and Biology.

In The Last Decade

F. Salzenstein

29 papers receiving 561 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
F. Salzenstein France 15 228 95 91 82 75 29 591
Jae-Chern Yoo South Korea 11 457 2.0× 112 1.2× 173 1.9× 35 0.4× 89 1.2× 35 1.1k
Mary L. Comer United States 14 432 1.9× 155 1.6× 53 0.6× 39 0.5× 43 0.6× 80 802
Éric Deléchelle France 11 391 1.7× 75 0.8× 92 1.0× 376 4.6× 64 0.9× 25 984
Xiaoheng Tan China 19 219 1.0× 200 2.1× 172 1.9× 35 0.4× 71 0.9× 105 1.1k
P. Bunel France 5 323 1.4× 52 0.5× 36 0.4× 214 2.6× 53 0.7× 8 654
Jeff Orchard Canada 16 461 2.0× 156 1.6× 57 0.6× 71 0.9× 82 1.1× 49 877
Weibin Liu China 14 344 1.5× 107 1.1× 71 0.8× 31 0.4× 26 0.3× 122 758
Y. Bouaoune France 4 293 1.3× 50 0.5× 34 0.4× 214 2.6× 41 0.5× 7 612
O. Zahran Egypt 16 442 1.9× 124 1.3× 79 0.9× 33 0.4× 84 1.1× 93 967

Countries citing papers authored by F. Salzenstein

Since Specialization
Citations

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

Fields of papers citing papers by F. Salzenstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of F. Salzenstein

This figure shows the co-authorship network connecting the top 25 collaborators of F. Salzenstein. A scholar is included among the top collaborators of F. Salzenstein 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 F. Salzenstein. F. Salzenstein 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.
Salzenstein, F. & Abdel‐Ouahab Boudraa. (2022). Multidimensional directional derivatives and AM-FM dual-band image demodulation by higher order Teager-Kaiser operators. Digital Signal Processing. 129. 103641–103641. 2 indexed citations
2.
Salzenstein, F., et al.. (2016). Comparison of envelope detection techniques in coherence scanning interferometry. Applied Optics. 55(24). 6763–6763. 16 indexed citations
3.
Montgomery, Paul, et al.. (2015). Multi-scale roughness measurement of cementitious materials using different optical profilers and window resizing analysis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9525. 95250Z–95250Z. 3 indexed citations
4.
5.
Salzenstein, F., Paul Montgomery, & Abdel‐Ouahab Boudraa. (2014). Local frequency and envelope estimation by Teager-Kaiser energy operators in white-light scanning interferometry. Optics Express. 22(15). 18325–18325. 14 indexed citations
6.
Montgomery, Paul, et al.. (2013). Implementation of a fringe visibility based algorithm in coherence scanning interferometry for surface roughness measurement. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8788. 87883G–87883G. 20 indexed citations
7.
Salzenstein, F., Abdel‐Ouahab Boudraa, & Thierry Chonavel. (2012). A new class of multi-dimensional Teager-Kaiser and higher order operators based on directional derivatives. Multidimensional Systems and Signal Processing. 24(3). 543–572. 12 indexed citations
8.
Collet, Christophe, et al.. (2010). Detection of Transient Signals in Lung Sounds: Local Approach Using a Markovian Tree with Frequency Selectivity. Journal of Signal Processing Systems. 65(3). 445–456. 2 indexed citations
9.
Boudraa, Abdel‐Ouahab, et al.. (2009). Higher order Teager-Kaiser operators for image analysis: Part I - A monocomponent image demodulation. 1041–1044. 4 indexed citations
10.
Belghith, Akram, et al.. (2009). Wheezing sounds detection using multivariate generalized gaussian distributions. 11. 541–544. 22 indexed citations
11.
Boudraa, Abdel‐Ouahab, et al.. (2009). A joint 2D AM–FM estimation based on higher order Teager–Kaiser energy operators. Signal Image and Video Processing. 5(1). 61–68. 12 indexed citations
12.
Salzenstein, F. & Abdel‐Ouahab Boudraa. (2008). Multi-dimensional higher order differential operators derived from the Teager–Kaiser energy-tracking function. Signal Processing. 89(4). 623–640. 8 indexed citations
13.
Salzenstein, F., Abdel‐Ouahab Boudraa, & Jean-Christophe Cexus. (2007). Generalized higher-order nonlinear energy operators. Journal of the Optical Society of America A. 24(12). 3717–3717. 19 indexed citations
14.
Hatt, Mathieu, F. Lamare, Nicolas Boussion, et al.. (2007). Fuzzy hidden Markov chains segmentation for volume determination and quantitation in PET. Physics in Medicine and Biology. 52(12). 3467–3491. 58 indexed citations
15.
Salzenstein, F. & C. Collet. (2006). Fuzzy Markov Random Fields versus Chains for Multispectral Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(11). 1753–1767. 41 indexed citations
16.
Salzenstein, F., et al.. (2005). Teager-Kaiser Energy and Higher-Order Operators in White-Light Interference Microscopy for Surface Shape Measurement. EURASIP Journal on Advances in Signal Processing. 2005(17). 11 indexed citations
17.
Boudraa, Abdel‐Ouahab, et al.. (2004). IF estimation using empirical mode decomposition and nonlinear Teager energy operator. 45–48. 45 indexed citations
18.
Boudraa, Abdel‐Ouahab, et al.. (2004). Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions. ELCVIA Electronic Letters on Computer Vision and Image Analysis. 4(1). 1–1. 52 indexed citations
19.
Salzenstein, F., et al.. (2003). 2D discrete high order energy operators for surface profiling using white light interferometry. 601–604 vol.1. 6 indexed citations
20.
Salzenstein, F. & Wojciech Pieczynski. (2002). Unsupervised Bayesian segmentation using hidden Markovian fields. 4. 2411–2414. 6 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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