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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Journal ArticleDOI
COVI3D: Automatic COVID-19 CT Image-Based Classification and Visualization Platform Utilizing Virtual and Augmented Reality Technologies
Samir Benbelkacem,Adel Oulefki,Sos S. Agaian,Nadia Zenati-Henda,Thaweesak Trongtirakul,Djamel Aouam,Mostefa Masmoudi,Mohamed Zemmouri +7 more
TL;DR: This article proposes designing an automatic VR and AR platform for the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic data analysis, classification, and visualization to address the above-mentioned challenges.
Patent
Systems, apparatus, and methods for bit level representation for data processing and analytics
TL;DR: In this paper, the authors describe a set of methods for denoising, enhancing, compressing, decompressing, storing, and transmitting digitized media such as text, audio, image, and video.
Proceedings ArticleDOI
Human visual system-based edge detection using image contrast enhancement and logarithmic ratio
Ali Almuntashri,Sos S. Agaian +1 more
TL;DR: The introduced algorithm integrates image enhancement, edge detection and logarithmic ratio filtering algorithms to develop an effective edge detection method and a parameter is introduced to control the level of detected edge details and functions as a primary threshold parameter.
Proceedings ArticleDOI
A novel method of testing image randomness with applications to image shuffling and encryption
TL;DR: Simulation results show that the proposed method is robust and effective in evaluating the degree of image randomness, and may often be more suitable for image applications than commonly used testing schemes designed for binary data like NIST 800-22 test suites.
Proceedings ArticleDOI
Three dimensional alpha weighted quadratic filter based image color contrast enhancement
TL;DR: A new spatial domain color contrast enhancement algorithm based on the three dimensional alpha weighted quadratic filter (3DAWQF) to utilize the characteristics of the nonlinear filter to enhance image contrast while recovering the color information is introduced.