Results 211 to 220 of about 4,542 (232)
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, 2017
Summary Shearlet transform, as a multi-scale and multi-directional transformation is highly capable of detecting features with different dips and has found several applications in image processing tasks.
Haleh Karbalaali +4 more
semanticscholar +1 more source
Summary Shearlet transform, as a multi-scale and multi-directional transformation is highly capable of detecting features with different dips and has found several applications in image processing tasks.
Haleh Karbalaali +4 more
semanticscholar +1 more source
Surface Defect Recognition for Metals Based on Feature Fusion of Shearlets and Wavelets
, 2015Surface defects of metals are often with complexity and diversity. Wavelet transform is effective to detect singularities, it is applicable for recognition of point defects.
Peng Zhou
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Shearlets as Multi-scale Radon Transforms
Sampling Theory in Signal and Image Processing, 2017We show that the 2D-shearlet transform is the composition of the affine Radon transform, a 1D-wavelet transform and a 1D-convolution.
BARTOLUCCI, FRANCESCA +3 more
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Optimally Sparse Multidimensional Representation Using Shearlets
SIAM Journal on Mathematical Analysis, 2007In this paper we show that shearlets, an affine-like system of functions recently introduced by the authors and their collaborators, are essentially optimal in representing 2-dimensional functions f which are $C^2$ except for discontinuities along $C^2 ...
K. Guo, D. Labate
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2015
In this chapter, we will provide a comprehensive overview of shearlet coorbit theory. We will present an almost self-contained introduction into coorbit theory which is the basis for all our investigations. We also discuss the group theoretical background of the continuous shearlet transform, and we explain how the shearlet transform can be combined ...
Sören Häuser +3 more
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In this chapter, we will provide a comprehensive overview of shearlet coorbit theory. We will present an almost self-contained introduction into coorbit theory which is the basis for all our investigations. We also discuss the group theoretical background of the continuous shearlet transform, and we explain how the shearlet transform can be combined ...
Sören Häuser +3 more
openaire +2 more sources
Face recognition using Shearlets
2012 IEEE 7th International Conference on Industrial and Information Systems (ICIIS), 2012In this paper we propose a novel statistical face recognition method that uses a new multiresolution analysis called Shearlet transform for facial texture features representation. In recent years Shearlet transform has emerged as the most successful framework for the efficient representation of multidimensional data in which directional information is ...
Ajit Danti, K. M. Poornima
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The Discrete Shearlet Transform: A New Directional Transform and Compactly Supported Shearlet Frames
IEEE Transactions on Image Processing, 2010It is now widely acknowledged that analyzing the intrinsic geometrical features of the underlying image is essential in many applications including image processing. In order to achieve this, several directional image representation schemes have been proposed.
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Biorthogonal Multiresolution Analysis of Shearlets
2009 First International Conference on Information Science and Engineering, 2009In this paper, we will give the framework of biorthogonal multiresolution analysis of shearlets in two dimensions, and study associated mathematical properties. Then, we will generalize the classical cascade algorithm.
Ji-zheng Di, Zhi-hui Shi
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2018 26th European Signal Processing Conference (EUSIPCO), 2018
In video coding, in-loop filtering has attracted attention due to its increasing coding performances. In this paper the shearlet-based loop filter is proposed using a sparsifying transform, the shearlet transform, which can identify the important structures of natural images such as edges in the sparse transform domain.
Thomas Wiegand +4 more
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In video coding, in-loop filtering has attracted attention due to its increasing coding performances. In this paper the shearlet-based loop filter is proposed using a sparsifying transform, the shearlet transform, which can identify the important structures of natural images such as edges in the sparse transform domain.
Thomas Wiegand +4 more
openaire +1 more source
Shearlet Features for Pedestrian Detection
Journal of Mathematical Imaging and Vision, 2018A long-time, hand-crafted features governed by a directional image analysis have been the base for the best performing pedestrian detection algorithms. In the past few years, approaches using convolutional neural networks have taken over the leadership concerning detection quality.
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