Results 51 to 60 of about 5,473 (223)
Quaternionic shearlet transform [PDF]
Optik, 2018 Abstract The shearlet transform has been shown to be a valuable and powerful time–frequency analyzing tool for optics and non-stationary signal processing. In this article, we propose a novel transform called quaternionic shearlet transform which is designed to represent quaternion-valued signals at different scales, locations and orientations.
Firdous A. Shah, Azhar Y. Tantary
openaire +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
core +1 more source
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
IEEE Access, 2020 Colon cancer identification is of great significance in medical diagnosis. Real-time, objective and accurate inspection results will facilitate medical professionals to explore symptomatic treatment promptly.
Meiyan Liang +4 more
doaj +1 more source
CHILDHOOD MEDULLOBLASTOMA DIAGNOSIS USING MULTISCALE FRAMEWORK
International Journal of Advances in Signal and Image Sciences, 2022 This paper proposes an efficient Shearlet Based Childhood MedulloBlastoma (SBCMB) detection system. It is a classification system that extracts prominent characteristics for childhood MedulloBlastoma diagnosis from a given collection of histopathological
Vishal Eswaran, Usha Eswaran
doaj +1 more source
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
, 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
core +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
Perceptual watermarking for Discrete Shearlet transform [PDF]
2014 5th European Workshop on Visual Information Processing (EUVIP), 2014 This paper presents a new perceptual watermarking model for Discrete Shearlet transform (DST). DST provides the optimal representation [10] of the image features based on multi-resolution and multi-directional analysis. This property can be exploited on for watermark embedding to achieve the watermarking imperceptibility by introducing the human visual
Baharak Ahmaderaghi +3 more
openaire +3 more sources
Convex multiclass segmentation with shearlet regularization [PDF]
International Journal of Computer Mathematics, 2013 Segmentation plays an important role in many preprocessing stages in image processing. Recently, convex relaxation methods for image multi-labeling were proposed in the literature. Often these models involve the total variation (TV) semi-norm as regularizing term.
Sören Häuser, Gabriele Steidl
openaire +2 more sources