Results 21 to 30 of about 1,095 (204)

Image Sequence Fusion and Denoising Based on 3D Shearlet Transform [PDF]

open access: yesJournal of Applied Mathematics, 2014
We propose a novel algorithm for image sequence fusion and denoising simultaneously in 3D shearlet transform domain. In general, the most existing image fusion methods only consider combining the important information of source images and do not deal ...
Liang Xu, Junping Du, Zhenhong Zhang
doaj   +2 more sources

Shearlet Transform and the Application in Image Processing

open access: yes, 2022
Shearlet is a multi-dimensional function used for sparse representation, which has many excellent characteristics such as multi-resolution and multi-direction. It can detect the position of singular points and the direction of singular curves, and is more sensitive to the geometric structure of the image.
Haitao H.   +3 more
openaire   +3 more sources

Light Field Reconstruction Using Shearlet Transform in TensorFlow

open access: yes2019 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
Yuan Gao 0008   +3 more
openaire   +3 more sources

Visual sensor image enhancement based on non-sub-sampled shearlet transform and phase stretch transform

open access: yesEURASIP Journal on Wireless Communications and Networking, 2019
Acquiring clear images is a requisite in visual sensor networks. Image enhancement is an effective way to improve image quality. In this paper, non-sub-sampled shearlet transform (NSST) multi-scale analysis is combined with phase stretch transform (PST ...
Ying Tong
doaj   +2 more sources

A three-dimensional microseismic downhole noise suppression based on polarization filtering method in Shearlet transform

open access: yesFrontiers in Earth Science, 2023
Microseismic noise suppression is widely used in the exploration of unconventional oil and gas resources. The effective microseismic downhole signals have extremely weak energy and are contaminated by strong interference, making data processing and ...
Li Han, Dongyan Wang, Pengjun Yu
doaj   +1 more source

Quaternionic shearlet transform [PDF]

open access: yesOptik, 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

The shearlet transform and Lizorkin spaces [PDF]

open access: yes, 2020
17
Bartolucci, Francesca   +2 more
openaire   +3 more sources

Use of the shearlet energy entropy and of the support vector machine classifier to process weak microseismic and desert seismic signals

open access: yesComptes Rendus. Géoscience, 2020
Low-amplitude signal detection is a key procedure in borehole microseismic and desert seismic exploration. Usually, signals are difficult to detect due to their low amplitude and noise contamination.
Li, Yue   +3 more
doaj   +1 more source

Digital Shearlet Transforms [PDF]

open access: yes, 2012
Over the past years, various representation systems which sparsely approximate functions governed by anisotropic features such as edges in images have been proposed. We exemplarily mention the systems of contourlets, curvelets, and shearlets. Alongside the theoretical development of these systems, algorithmic realizations of the associated transforms ...
Gitta Kutyniok   +2 more
openaire   +3 more sources

Image fusion based on discrete Shearlet transform.

open access: yes, 2023
Image fusion based on discrete Shearlet transform.
S. Abisha (15188270)   +3 more
core   +1 more source

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