Results 41 to 50 of about 726,843 (203)
Remote Sensing Image Denoising Based on Gaussian Curvature and Shearlet Transform
IEEE Access, 2023 Model-based image denoising methods are well suited for use as image processors in remote sensing systems such as satellites due to their well-developed mathematical theory and low computational cost, but these methods can often only deal with a single ...
Libo Cheng, Pengyu Chen
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Linearized Riesz transform and quasi-monogenic shearlets [PDF]
International Journal of Wavelets, Multiresolution and Information Processing, 2014 The only quadrature operator of order two on L2(ℝ2) which covaries with orthogonal transforms, in particular rotations is (up to the sign) the Riesz transform. This property was used for the construction of monogenic wavelets and curvelets. Recently, shearlets were applied for various signal processing tasks.
Sören Häuser +2 more
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Advanced Intelligent Systems, Volume 5, Issue 11, November 2023., 2023 Expectation‐maximization algorithm generative adversarial network (EMA‐GAN) is proposed to fuse images from different modalities. This is an EM learning framework based on GAN that maximizes the likelihood of fused results and estimates potential variables.
Xiuliang Xi +5 more
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GF-3 SAR IMAGE DESPECKLING BASED ON THE IMPROVED NON-LOCAL MEANS USING NON-SUBSAMPLED SHEARLET TRANSFORM [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 GF-3 synthetic aperture radar (SAR) images are rich in information and have obvious sparse features. However, the speckle appears in the GF-3 SAR images due to the coherent imaging system and it hinders the interpretation of images seriously.
R. Shi, Z. Sun
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ACM Transactions on Mathematical Software, 2016 Wavelets and their associated transforms are highly efficient when approximating and analyzing one-dimensional signals. However, multivariate signals such as images or videos typically exhibit curvilinear singularities, which wavelets are provably deficient in sparsely approximating and also in analyzing in the sense of, for instance, detecting their ...
Gitta Kutyniok +2 more
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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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IEEE Access, 2020 Colon cancer identification is of great significance in medical diagnosis. Real-time, objective and accurate inspection results will facilitate medical professionals to explore symptomatic treatment promptly.
Meiyan Liang +4 more
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Homogeneous approximation property for continuous shearlet transforms in higher dimensions
Journal of Inequalities and Applications, 2016 This paper is concerned with the generalization of the homogeneous approximation property (HAP) for a continuous shearlet transform to higher dimensions. First, we give a pointwise convergence result on the inverse shearlet transform in higher dimensions.
Yu Su, Wanchang Zhang, Wenting Su
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Multivariate Shearlet Transform, Shearlet Coorbit Spaces and Their Structural Properties [PDF]
, 2012 This chapter is devoted to the generalization of the continuous shearlet transform to higher dimensions as well as to the construction of associated smoothness spaces and to the analysis of their structural properties, respectively. To construct canonical scales of smoothness spaces, so-called shearlet coorbit spaces, and associated atomic ...
Stephan Dahlke +2 more
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A novel feature descriptor based on the shearlet transform [PDF]
2011 18th IEEE International Conference on Image Processing, 2011 Problems such as image classification, object detection and recognition rely on low-level feature descriptors to represent visual information. Several feature extraction methods have been proposed, including the Histograms of Oriented Gradients (HOG), which captures edge information by analyzing the distribution of intensity gradients and their ...
William Robson Schwartz +3 more
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