Results 51 to 60 of about 3,713 (248)
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
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Morphological Edge Detection Algorithm of Colon Pathological Sections Based on Shearlet
Journal of Mathematics, 2022 This paper proposes an idea of combining the Meyer Shearlet and mathematical morphology to produce the edge detection of pathological sections of the colon. First, the method of constructing a class of sufficiently smooth sigmoid functions along with its
Shasha Li +3 more
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IEEE AccessThis paper introduces an innovative content-based image retrieval system for precise and effective retrieval of satellite images. The system integrates liquid autoencoders with shearlet transforms to derive robust feature representations from satellite ...
Sai Bhargav Kasetty, K. Rajakumar
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Infrared and Visible Image Fusion Based on Co-Occurrence Analysis Shearlet Transform
Remote Sensing, 2022 This study based on co-occurrence analysis shearlet transform (CAST) effectively combines the latent low rank representation (LatLRR) and the regularization of zero-crossing counting in differences to fuse the heterogeneous images.
Biao Qi +6 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
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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
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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
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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
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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
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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
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