Lute Kamstra
- Computer Vision and Pattern Recognition top 5%
- Computer Graphics and Computer-Aided Design top 10%
- Signal Processing
- Media Technology
- Information Systems
- Co-authors
- H.J.A.M. HeijmansPaul M. de Zeeuw
- Topics
- Image and Signal Denoising Methods (5 papers)Advanced Data Compression Techniques (4 papers)Chaos-based Image/Signal Encryption (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignMedia Technology
- Journals
- IEEE Transactions on Image ProcessingJournal of Mathematical Imaging and VisionData Archiving and Networked Services (DANS)
- Partner nations
- Netherlands
In The Last Decade
Lute Kamstra
7 papers receiving 323 citations
Peers
Comparison fields: 5 of 19
- Computer Vision and Pattern Recognition 352
- Computer Graphics and Computer-Aided Design 12
- Signal Processing 11
- Media Technology 11
- Information Systems 7
Countries citing papers authored by Lute Kamstra
This map shows the geographic impact of Lute Kamstra'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 Lute Kamstra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lute Kamstra more than expected).
Fields of papers citing papers by Lute Kamstra
This network shows the impact of papers produced by Lute Kamstra. 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 Lute Kamstra. The network helps show where Lute Kamstra may publish in the future.
Co-authorship network of co-authors of Lute Kamstra
This figure shows the co-authorship network connecting the top 25 collaborators of Lute Kamstra. A scholar is included among the top collaborators of Lute Kamstra 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 Lute Kamstra. Lute Kamstra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 327 | |
| 2 | 2 | |
| 3 | Wavelet techniques for reversible data embedding into images | 5 |
| 4 | 9 | |
| 5 | Reversible Data Embedding Based on the Haar Wavelet Decomposition | 0 |
| 6 | 8 | |
| 7 | Discrete wavelet transforms over finite sets which are translation invariant | 2 |
| 8 | Wavelets and their applications | 3 |
About Lute Kamstra
Lute Kamstra is a scholar working on Computer Vision and Pattern Recognition, Applied Mathematics and Signal Processing, having authored 8 papers that have together received 356 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (5 papers), Advanced Data Compression Techniques (4 papers) and Chaos-based Image/Signal Encryption (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (352 citations), Computer Graphics and Computer-Aided Design (12 citations) and Media Technology (11 citations). Lute Kamstra has collaborated with scholars based in Netherlands. Frequent co-authors include H.J.A.M. Heijmans and Paul M. de Zeeuw. Their work appears in journals such as IEEE Transactions on Image Processing, Journal of Mathematical Imaging and Vision and Data Archiving and Networked Services (DANS).
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.