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Completed Extremely Nonnegative DMD for Color Texture Classification
2020
IEEE Access
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INDEX TERMS Color texture representation, dense micro-block difference (DMD), extremely nonnegative multiresolution, texture classification. 103034 This work is licensed under a Creative Commons Attribution ...
To alleviate this problem, we propose a novel color texture representation method based on Completed Extremely Nonnegative DMD (CEN-DMD) in this paper. ...
Multiresolution representation of color texture images is achieved by differential between different scales of micro-blocks. We named it Extremely Nonnegative DMD (EN-DMD). ...
doi:10.1109/access.2020.2998926
fatcat:yp44uzblujd4fkuz7zkzhwdjdy
A translation- and scale-invariant adaptive wavelet transform
2000
IEEE Transactions on Image Processing
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task of scale-invariant texture identification. ...
Furthermore, as an application, we define a new textural feature in the framework of our adaptive wavelet decomposition, show its stability to shift and scaling, and demonstrate its efficiency for the ...
for texture classification, segmentation and recognition. ...
doi:10.1109/83.887977
pmid:18262947
fatcat:wstv6bkkonfkbok4flzcbpsmcm
A multi-scale comparison of texture descriptors extracted from the Wavelet and Curvelet domains for small bowel tumor detection in Capsule Endoscopy exams
[chapter]
2009
International Federation for Medical and Biological Engineering Proceedings
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Therefore, in the present paper it is proposed a frame classification scheme, based in different combinations of texture descriptors taken at different detail levels of the Discrete Wavelet Transform and ...
Discrete Curvelet Transform domains, in order to compare the classification performance of these multi-resolution representations of the information within the CE frames. ...
being a multiresolution representation of the information within the image. ...
doi:10.1007/978-3-642-03882-2_410
fatcat:fykb5xqmxfdn5iczbd2lfjknnu
A multiresolution clinical decision support system based on fractal model design for classification of histological brain tumours
2015
Computerized Medical Imaging and Graphics
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A clinical decision support system that exploits the subband textural fractal characteristics for best bases selection of meningioma brain histopathological image classification is proposed. ...
Each subband is analysed using its fractal dimension instead of energy, which has the advantage of being less sensitive to image intensity and abrupt changes in tissue texture. ...
We are concerned more with a better representation of the texture characteristics at each decomposition; therefore, this work presents an overcomplete tree-structured wavelet packet representation by omitting ...
doi:10.1016/j.compmedimag.2014.05.013
pmid:24962336
fatcat:ppkeqkrjh5gzxekj4ael2yf2l4
Editorial for Special Issue "Hyperspectral Imaging and Applications"
2019
Remote Sensing
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This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories, Data Unmixing, Spectral variability, Target Detection, Hyperspectral Image Classification ...
Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. ...
Qu This paper develops a Component substitution (CS) and multiresolution analysis (MRA)-based hybrid framework based on intrinsic image decomposition and weighted least squares filter for hyperspectral ...
doi:10.3390/rs11172012
fatcat:c23u3rahgjhctowk5xwllt2qea
Front Matter: Volume 9643
2015
Image and Signal Processing for Remote Sensing XXI
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. The last two digits indicate publication order within the volume using a Base 36 numbering system employing both numerals and letters. ...
and simulated hyperspectral
images [9643-20]
SESSION 5
HYPERSPECTRAL IMAGE ANALYSIS II
9643 0L
Low-dimensional representations of hyperspectral data for use in CRF-based classification
[9643-21 ...
[9643-5]
SESSION 3
IMAGE ENHANCEMENT AND FILTERING
9643 0B
Multiscale statistical image destriping algorithm [9643-11]
9643 0C
Noise correlation-based adaptive polarimetric image representation ...
doi:10.1117/12.2225976
fatcat:rvhcmbnlg5cflmftjesqzoq62m
Minimum Probability of Error Image Retrieval
2004
IEEE Transactions on Signal Processing
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Index Terms-Bayesian methods, color and texture, expectation-maximization, feature selection, image retrieval, image similarity, minimum probability of error, mixture models, multiresolution, optimal retrieval ...
Minimum probability of error (MPE) is adopted as the optimality criterion and retrieval formulated as a problem of statistical classification. ...
Index Terms-Bayesian methods, color and texture, expectation-maximization, feature selection, image retrieval, image similarity, minimum probability of error, mixture models, multiresolution, optimal retrieval ...
doi:10.1109/tsp.2004.831125
fatcat:2bmgag7qjjgynft2c3o7cl6v6y
A Review of Machine-Vision-Based Analysis of Wireless Capsule Endoscopy Video
2012
Diagnostic and Therapeutic Endoscopy
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For example, there are radiographic projection-based images (e.g., X-rays and PET scans), tomography-based images (e.g., MRT and CT scans), and photography-based images (e.g., endoscopy, dermatology, and ...
In order to train a machine to understand the semantics of an image, the image contents need to be translated into numerical form first. The numerical form of the image is known asimage abstraction. ...
Semantic-based image retrieval was introduced in 2000s to create semantic content representation for images. ...
doi:10.1155/2012/418037
pmid:23197930
pmcid:PMC3502844
fatcat:34xe2ifqnvdm5batsjncl236bu
Content-Based Image Retrieval Using Multiresolution Color and Texture Features
2008
IEEE transactions on multimedia
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Index Terms-Content-based image retrieval, multiresolution representation, color and texture features. 1520-9210/$25.00 ...
In this paper, we propose a content-based image retrieval method based on an efficient combination of multiresolution color and texture features. ...
12] , and [13] , which are used for image detection, texture analysis and classification, and image retrieval by using multiresolution analyses, respectively. ...
doi:10.1109/tmm.2008.2001357
fatcat:5rtqayp4m5dzzors7o6yrnjyvy
Anomaly Detection Based on Wavelet Domain GARCH Random Field Modeling
2007
IEEE Transactions on Geoscience and Remote Sensing
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Index Terms-Anomaly detection, Gaussian Markov random field (GMRF), Generalized Autoregressive Conditional Heteroscedasticity (GARCH), image segmentation, image texture analysis, matched subspace detector ...
, multiscale representation, object recognition. ...
The multiresolution representation and clutter modeling based on multiscale GARCH model allow for correlation in and between layers of the multiresolution representation in addition to the GARCH characteristics ...
doi:10.1109/tgrs.2007.893741
fatcat:7pzvs3o6yfa2jkq44wwfpzsroi
Modeling Bidirectional Texture Functions with Multivariate Spherical Radial Basis Functions
2011
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper presents a novel parametric representation for bidirectional texture functions. ...
an intrinsic and efficient representation for heterogenous materials. ...
v Á : ð6Þ Note that (6) is similar to many factorization-based representations for BRDFs, e.g., principal component analysis [14] and nonnegative matrix factorization [47] , but our multivariate representation ...
doi:10.1109/tpami.2010.211
pmid:21135438
fatcat:gy27xmnzbbgyld6alt4g4ifnee
Factorization-based Active Contour for Water-Land SAR image segmentation via the Fusion of Features
2019
IEEE Access
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INDEX TERMS Synthetic aperture radar (SAR), remote sensing, image segmentation, active contour, edge detector, matrix decomposition techniques, texture feature. ...
The edge-based active contour model, proposed by Kass et al. [12] moves the explicit parametric curves to extract objects in images. ...
There are many methods based on texture features for SAR image segmentation [25] , [26] , [37] , SAR image classification [38] and registration [39] . ...
doi:10.1109/access.2019.2905847
fatcat:z3xyzzgajbgtllfvsvezxogj5u
A Review of Image Denoising Methods
2015
Journal of Engineering Science and Technology Review
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Images are one of essential representations in every field like education, agriculture, geosciences, aerospace, surveillance, entertainment etc by means of electronic or print media. ...
These methods have been categorized on the bases of techniques used. ...
Statistical Modeling Based Image Denoising
Due the sparseness property of multiresolution image
representation in non-Gaussian statistics for wavelet
coefficients, multiresolution image representation ...
doi:10.25103/jestr.085.07
fatcat:4c4f3oz3wzakhaitav3k5ktdp4
Non-decimated Complex Wavelet Spectral Tools with Applications
[article]
2019
arXiv
pre-print
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diagnostic and classification of digital mammogram images using the fractality of digitized images of the background tissue. ...
of classification. ...
Phase-based Statistics for Classification Analysis In the area of Fourier representations, there is a considerable of interest about the information the phase carries about signals or images [Oppenheim ...
arXiv:1902.01032v1
fatcat:as7now4ixjfd7b6ry4c2k32sj4
Adaptive wavelet graph model for Bayesian tomographic reconstruction
2002
IEEE Transactions on Image Processing
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The parameters of this distribution are selected adaptively using nonlinear classification of coarse scale data. The nonlinear adaptation mechanism is based on a set of training images. ...
Index Terms-Bayesian tomography, image reconstruction, wavelet-based image modeling. ...
INTRODUCTION A MAJOR challenge for Bayesian image reconstruction methods is the design of image prior models that accurately account for edges as well as uniform and textured regions in images, yet result ...
doi:10.1109/tip.2002.801586
pmid:18244672
fatcat:4p2qlqpq7rhkdph34vvo7ucbsi
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