M
Manos Papadakis
Researcher at University of Houston
Publications - 71
Citations - 822
Manos Papadakis is an academic researcher from University of Houston. The author has contributed to research in topics: Wavelet & Multiresolution analysis. The author has an hindex of 15, co-authored 69 publications receiving 772 citations. Previous affiliations of Manos Papadakis include University of Ioannina & National and Kapodistrian University of Athens.
Papers
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Journal ArticleDOI
Perinasal Imaging of Physiological Stress and Its Affective Potential
TL;DR: A novel framework for quantifying physiological stress at a distance via thermal imaging that associates high stress levels with novice surgeons, while low stress levels are associated with experienced surgeons, raising the possibility for an affective measure (stress) to assist in efficacy determination.
Journal ArticleDOI
Image denoising using a tight frame
Lixin Shen,Manos Papadakis,Ioannis A. Kakadiaris,I. Konstantinidis,Donald J. Kouri,David K. Hoffman +5 more
TL;DR: A general mathematical theory for lifting frames is presented that allows us to modify existing filters to construct new ones that form Parseval frames, and a new image denoising algorithm is proposed, tailored to the specific properties of these new frame filters.
Journal ArticleDOI
The geometry and the analytic properties of isotropic multiresolution analysis
TL;DR: The main results are the characterization of IMRAs in terms of the Lax–Wiener Theorem, and the characterization and application of IMRA wavelets to 2D and 3D-texture segmentation in natural and biomedical images.
Journal ArticleDOI
Automatic Morphological Reconstruction of Neurons from Multiphoton and Confocal Microscopy Images Using 3D Tubular Models
Alberto Santamaria-Pang,Paul Hernandez-Herrera,Manos Papadakis,Peter Saggau,Ioannis A. Kakadiaris +4 more
TL;DR: A novel representation, the Minimum Shape-Cost (MSC) Tree, is introduced that approximates the dendrite centerline with sub-voxel accuracy and is demonstrated to be the uniqueness of such a shape representation as well as its computational efficiency.
Proceedings ArticleDOI
Image denoising using a tight frame
Lixin Shen,Manos Papadakis,Ioannis A. Kakadiaris,L. Konstantinidis,Donald J. Kouri,D. Hoffman +5 more
TL;DR: A general mathematical theory for lifting frames is presented that allows us to modify existing filters to construct new ones that form Parseval frames, and a new image denoising algorithm is proposed, tailored to the specific properties of these new frame filters.