Results 71 to 80 of about 6,454 (268)
Irregular Shearlet Frames: Geometry and Approximation Properties
, 2010 Recently, shearlet systems were introduced as a means to derive efficient encoding methodologies for anisotropic features in 2-dimensional data with a unified treatment of the continuum and digital setting.
Kittipoom, P., Kutyniok, G., Lim, W.
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Use of the Shearlet Transform and Transfer Learning in Offline Handwritten Signature Verification and Recognition [PDF]
Sahand Communications in Mathematical Analysis, 2020 Despite the growing growth of technology, handwritten signature has been selected as the first option between biometrics by users. In this paper, a new methodology for offline handwritten signature verification and recognition based on the Shearlet ...
Atefeh Foroozandeh +2 more
doaj +1 more source
A Hybrid Approach for CT Image Noise Reduction Combining Method Noise-CNN and Shearlet Transform
Biomedical & Pharmacology JournalThe presence of gaussian noise commonly weakens the diagnostic precision of low-dose CT imaging. A novel CT image denoising technique that integrates the non-subsampled shearlet transform (NSST) with Bayesian thresholding, and incorporates a modern ...
Swapna Katta +3 more
semanticscholar +1 more source
All the Groups of Signal Analysis from the (1+1)-affine Galilei Group [PDF]
, 2011 We study the relationship between the (1+1)-affine Galilei group and four groups of interest in signal analysis and image processing, viz., the wavelet or the affine group of the line, the Weyl-Heisenberg, the shearlet and the Stockwell groups.
Ali, S. Twareque +1 more
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Image fusion based on shift invariant shearlet transform and stacked sparse autoencoder
Journal of Algorithms & Computational Technology, 2018 Stacked sparse autoencoder is an efficient unsupervised feature extraction method, which has excellent ability in representation of complex data. Besides, shift invariant shearlet transform is a state-of-the-art multiscale decomposition tool, which is ...
Peng-Fei Wang +3 more
doaj +1 more source
Scale Invariant Interest Points with Shearlets
, 2016 Shearlets are a relatively new directional multi-scale framework for signal analysis, which have been shown effective to enhance signal discontinuities such as edges and corners at multiple scales.
De Vito, Ernesto +3 more
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Shearlet-Based Structure-Aware Filtering for Hyperspectral and LiDAR Data Classification
Journal of remote sensing, 2021 The joint interpretation of hyperspectral images (HSIs) and light detection and ranging (LiDAR) data has developed rapidly in recent years due to continuously evolving image processing technology. Nowadays, most feature extraction methods are carried out
S. Jia, Z. Zhan, Meng Xu
semanticscholar +1 more source
Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning
Journal of Imaging, 2016 The Gleason grading system is generally used for histological grading of prostate cancer. In this paper, we first introduce using the Shearlet transform and its coefficients as texture features for automatic Gleason grading.
Hadi Rezaeilouyeh, Mohammad H. Mahoor
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Cone-Adapted Shearlets and Radon Transforms [PDF]
, 2020 19 pages, 3 ...
Bartolucci F., De Mari F., De Vito E.
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, 2012 Anisotropic decompositions using representation systems based on parabolic scaling such as curvelets or shearlets have recently attracted significantly increased attention due to the fact that they were shown to provide optimally sparse approximations of
Grohs, Philipp, Kutyniok, Gitta
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