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.
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NPCR and UACI Randomness Tests for Image Encryption
TL;DR: The question of whether a given NPCR/UACI score is sufficiently high such that it is not discernible from ideally encrypted images is answered by comparing actual NPCR and UACI scores with corresponding critical values.
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Human-Visual-System-Inspired Underwater Image Quality Measures
TL;DR: A new nonreference underwater image quality measure (UIQM) is presented, which comprises three underwater image attribute measures selected for evaluating one aspect of the underwater image degradation, and each presented attribute measure is inspired by the properties of human visual systems (HVSs).
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Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy
TL;DR: The presented algorithms use the fact that the relationship between stimulus and perception is logarithmic and afford a marriage between enhancement qualities and computational efficiency to choose the best parameters and transform for each enhancement.
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Local Shannon entropy measure with statistical tests for image randomness
TL;DR: The proposed local Shannon entropy measure overcomes several weaknesses of the conventional global Shannon entropyMeasure, including unfair randomness comparisons between images of different sizes, failure to discern image randomness before and after image shuffling, and possible inaccurate scores for synthesized images.
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Transform-based image enhancement algorithms with performance measure
TL;DR: A new class of the "frequency domain"-based signal/image enhancement algorithms including magnitude reduction, log-magnitude reduction, iterative magnitude and a log-reduction zonal magnitude technique, based on the so-called sequency ordered orthogonal transforms, which include the well-known Fourier, Hartley, cosine, and Hadamard transforms.