S
Sos S. Agaian
Researcher at City University of New York
Publications - 582
Citations - 10193
Sos S. Agaian is an academic researcher from City University of New York. The author has contributed to research in topics: Image processing & Computer science. The author has an hindex of 38, co-authored 532 publications receiving 8216 citations. Previous affiliations of Sos S. Agaian include College of Staten Island & University of Texas System.
Papers
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Proceedings ArticleDOI
Optimal color image restoration: Wiener filter and quaternion Fourier transform
TL;DR: This paper analyzes the linear model of the signal and image degradation with an additive independent noise and the optimal filtration of the signals and images in the frequency domain and in the quaternion space.
Proceedings ArticleDOI
Stego sensitivity measure and multibit plane based steganography using different color models
TL;DR: A new secure high capacity palette based steganographic method used to embed in multiple bit planes using different color models that was proven to be immune to Chi-square and Pairs Analysis steganalysis attacks and secure against detection from RS Steganalysis.
Proceedings ArticleDOI
Coordinate Logic Transforms and their Use in the Detection of Edges within Binary and Grayscale Images
TL;DR: A new measure and detection technique are introduced, enhancing the capabilities of the basic CL transform for the application of detecting edges within 2D signals (images), Applicable to binary and grayscale images.
Proceedings ArticleDOI
Alpha-trimmed image estimation for JPEG steganography detection
TL;DR: The alpha-trimmed method estimates steganographic messages within images in the spatial domain and provide flexibility for classifying various steganography methods in the JPEG compression domain results in better separability between clean and steganographers classes.
Journal ArticleDOI
Virtual Reality visualization for computerized COVID-19 lesion segmentation and interpretation.
Adel Oulefki,Sos S. Agaian,Thaweesak Trongtirakul,Samir Benbelkacem,Djamel Aouam,Nadia Zenati-Henda,Mohamed lamine Abdelli +6 more
TL;DR: In this paper, the authors combine CT imaging tools and Virtual Reality (VR) technology and generate an automatize system for accurately screening COVID-19 disease and navigating 3D visualizations of medical scenes.