Results 91 to 100 of about 3,242 (211)
Construction of Meyer Wavelet Using Fully Smooth Sigmiod Function
Journal of Harbin University of Science and Technology, 2019 In order to obtain better smooth effect in signal or image reconstruction, the regularity or continuous differentiability of wavelet must be increased as much as possible.
SHAO Yun-hong, DENG Cai-xia, HE Peng
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An Infrared and Visible Image Fusion Algorithm Based on LSWT-NSST
IEEE Access, 2020 Regarding the problems of image distortion, edge blurring, Gibbs phenomena in the traditional wavelet transform algorithm and the loss of subtle features in the Non-Subsampled Shearlet Transform (NSST), and considering the physical characteristics of ...
Li Junwu, Binhua Li, Yaoxi Jiang
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A Novel HDR Image Zero-Watermarking Based on Shift-Invariant Shearlet Transform [PDF]
, 2021 Shanshan Shi +3 more
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Sparse Regularization Based on Orthogonal Tensor Dictionary Learning for Inverse Problems
Mathematical Problems in Engineering, Volume 2024, Issue 1, 2024.In seismic data processing, data recovery including reconstruction of the missing trace and removal of noise from the recorded data are the key steps in improving the signal‐to‐noise ratio (SNR). The reconstruction of seismic data and removal of noise becomes a sparse optimization problem that can be solved by using sparse regularization.
Diriba Gemechu, Francisco Rossomando
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Asymptotic Analysis of Shearlet Transfom for Inpainting
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2018 Supply of missing data, also known as inpainting, is an important application of image processing.Wavelets are commonly used for inpainting algorithms. Shearlet transform which is an affinetransformation is the improvement of the wavelet transform.
Süleyman Çetinkaya +2 more
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Applied Sciences, 2019 A new feature extraction technique called DNST-GLCM-KSR (discrete non-separable shearlet transform-gray-level co-occurrence matrix-kernel spectral regression) is presented according to the direction and texture information of surface defects of ...
Xiaoming Liu +3 more
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Radon transform intertwines shearlets and wavelets
, 2017 26 pages, 1 ...
Bartolucci, Francesca +2 more
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AIP AdvancesTo solve the problems of noise coverage defect and low contrast between the defect and the background of ZrO2 ceramic bearing balls, a surface defect extraction algorithm based on shearlet transform image enhancement for ZrO2 ceramic bearing balls is ...
Dahai Liao +5 more
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Light Field Reconstruction Using Shearlet Transform in TensorFlow
2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2019 Shearlet Transform (ST) is one of the most effective approaches for light field reconstruction from Sparsely-Sampled Light Fields (SSLFs). This demo paper presents a comprehensive implementation of ST for light field reconstruction using one of the most popular machine learning libraries, i.e. Tensor Flow. The flexible architecture of TensorFlow allows
Gao, Yuan +3 more
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Suppressing seismic random noise based on non-subsampled shearlet transform and improved FFDNet
Frontiers in Earth ScienceTraditional denoising methods often lose details or edges, such as Gaussian filtering. Shearlet transform is a multi-scale geometric analysis tool which has the advantages of multi-resolution and multi-directivity.
Hua Fan, Yang Zhang, Wenxu Wang, Tao Li
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