Results 101 to 110 of about 2,599 (188)
GPR data noise attenuation based on the Shearlet transform
矿业科学学报, 2017 When using ground penetrating radar(GPR) to detect the underground target distribution, valid signal in receiving data tend to be susceptible to noise and the interference of air-ground waves, which will affect the accuracy of target recognition and ...
Zheng Jing +4 more
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Multi-Focus Image Fusion Algorithm in Sensor Networks
IEEE Access, 2018 Most imaging systems have a limited depth-of-field in the sensor networks that consist of multiple visual sensors. Due to different object distances, not every object can be clearly imaged by a single sensor.
Ying Tong, Jin Chen
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Facial Expression Recognition Based on Discrete Separable Shearlet Transform and Feature Selection
Algorithms, 2018 In this paper, a novel approach to facial expression recognition based on the discrete separable shearlet transform (DSST) and normalized mutual information feature selection is proposed. The approach can be divided into five steps.
Yang Lu, Shigang Wang, Wenting Zhao
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Frontiers in Remote SensingSatellite image analysis is essential for remote sensing analysis. Two types of data are captured via satellite: Synthetic Aperture Radar (SAR) imagery (which has structure) and multispectral imagery (which contains spectral information), so ...
Sai Bhargav Kasetty, Rajakumar Krishnan
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Radon transform intertwines shearlets and wavelets
, 2017 26 pages, 1 ...
Bartolucci, Francesca +2 more
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Remote SensingThis study introduces a novel multi-channel predictive deconvolution method enhanced by Shearlet-based sparse regularization, aimed at improving the accuracy and stability of subsurface seismic imaging, particularly in offshore wind farm site assessments.
Yang Zhang +5 more
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Comparing Undecimated Wavelet, Nonsubsampled Contourlet and Shearlet for Sar Images Despeckling
Majlesi Journal of Electrical EngineeringSynthetic Aperture Radar (SAR) images suffer of multiplicative speckle noise, which damages the radiometric resolution of SAR images and makes the data interpretation difficult.
Saeed Jafari +2 more
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A New Shearlet Framework for Image Denoising
Iranian Journal of Electrical and Electronic Engineering, 2016 Traditional noise removal methods like Non-Local Means create spurious boundaries inside regular zones. Visushrink removes too many coefficients and yields recovered images that are overly smoothed.
E. Ehsaeyan
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Medical Image Fusion Based on Fast Finite Shearlet Transform and Sparse Representation. [PDF]
Comput Math Methods Med, 2019 Tan L, Yu X.
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Aiding the Digital Mammogram for Detecting the Breast Cancer Using Shearlet Transform and Neural Network [PDF]
Asian Pac J Cancer Prev, 2018 P S, R T.
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