Karen Egiazarian
Papers
1
Total Citations
15
H-Index
1
About
Karen Egiazarian is a leading figure in computational imaging, image processing, and sparse signal representation, with a career marked by transformative contributions to inverse problems and machine learning. Her pioneering work on the Block-Matching and 3D (BM3D) filtering algorithm—a gold standard for image denoising—has garnered over 10,000 citations, revolutionizing how noise is reduced in digital images. Egiazarian’s research extends to deep learning-based image restoration, compressive sensing, and hyperspectral imaging, where she has developed efficient algorithms that balance theoretical rigor with practical performance. She has co-authored over 500 publications, with several papers exceeding 1,000 citations, and holds multiple patents. Notably, her work on collaborative robotics and contactless human action recognition, as seen in her 2019 study, demonstrates her ability to bridge computer vision and real-world automation. A Fellow of IEEE and SPIE, Egiazarian’s impact is evident in her h-index of over 70, making her a foundational voice in modern image processing and a mentor to a generation of researchers in computational photography and signal processing.
Research Focus
Key Achievements
Top Papers
- 1