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Two-stage image denoising by principal component analysis with local pixel grouping

13 years 9 months ago

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Lei Zhang 0006, Weisheng Dong, David Zhang, Guangm...

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Id	Views	Title	Status

1	314	Two-stage image denoising by principal component analysis with local pixel grouping	claim
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3	220	Online finger-knuckle-print verification for personal authentication	claim
4	213	Real-time traffic sign recognition from video by class-specific discriminative features	claim
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7	184	Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images	claim
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11	171	A binarization method with learning-built rules for document images produced by cameras	claim
12	170	Sparsity preserving projections with applications to face recognition	claim
13	165	Active contours driven by local image fitting energy	claim
14	163	Optimal feature selection for support vector machines	claim
15	163	A comparative evaluation of interactive segmentation algorithms	claim
16	160	Homeomorphic alignment of weighted trees	claim
17	158	Out-of-bag estimation of the optimal sample size in bagging	claim
18	156	Semi-supervised clustering with metric learning: An adaptive kernel method	claim
19	156	The hyperbolic smoothing clustering method	claim
20	153	Parametric estimation of affine deformations of planar shapes
21	151	Coupled region-edge shape priors for simultaneous localization and figure-ground segmentation	claim
22	148	Registration and interactive planar segmentation for stereo images of polyhedral scenes	claim
23	147	A semi-supervised approach to space carving	claim
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25	146	High resolution partial fingerprint alignment using pore-valley descriptors	claim
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27	144	Classifying transformation-variant attributed point patterns	claim
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29	141	Salient feature and reliable classifier selection for facial expression classification	claim
30	141	On the vulnerability of face verification systems to hill-climbing attacks	claim
31	139	An adaptive unsupervised approach toward pixel clustering and color image segmentation	claim
32	135	Revisiting priority queues for image analysis	claim
33	133	Adaptive fingerprint pore modeling and extraction	claim
34	133	Familiarity based unified visual attention model for fast and robust object recognition	claim
35	129	Color space normalization: Enhancing the discriminating power of color spaces for face recognition	claim
36	129	Denoising and recognition using hidden Markov models with observation distributions modeled by hidden Markov trees	claim
37	129	Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach	claim
38	128	3D object classification using salient point patterns with application to craniofacial research	claim
39	126	Discriminability and reliability indexes: Two new measures to enhance multi-image face recognition	claim
40	124	The regular polygon detector	claim
41	123	Personalized text snippet extraction using statistical language models	claim
42	123	Enabling scalable spectral clustering for image segmentation	claim
43	120	Real-time 2D+3D facial action and expression recognition	claim
44	119	Bisection approach for pixel labelling problem	claim
45	119	Automatic color constancy algorithm selection and combination	claim
46	118	Clothing-invariant gait identification using part-based clothing categorization and adaptive weight control	claim
47	116	Secret image sharing based on cellular automata and steganography	claim
48	116	Effective segmentation and classification for HCC biopsy images	claim
49	114	A multi-scale framework for adaptive binarization of degraded document images	claim
50	112	Scene categorization via contextual visual words	claim
51	110	Action categorization with modified hidden conditional random field	claim
52	110	Object classification by fusing SVMs and Gaussian mixtures	claim
53	109	Analysis of multi-agent activity using petri nets	claim
54	106	Information theoretic novelty detection	claim
55	105	A novel iterative shape from focus algorithm based on combinatorial optimization	claim
56	102	Hand gesture recognition based on dynamic Bayesian network framework	claim
57	101	On-line independent support vector machines	claim
58	100	Handwritten document image segmentation into text lines and words	claim
59	99	Interactive image segmentation using probabilistic hypergraphs	claim
60	99	Learn++.MF: A random subspace approach for the missing feature problem	claim
61	98	Mountain c-regressions method	claim
62	98	A tree-structured framework for purifying "complex" clusters with structural roles of individual data	claim
63	97	Approximate input sensitive algorithms for point pattern matching	claim
64	96	People detection through quantified fuzzy temporal rules	claim
65	95	Image replica detection system utilizing R-trees and linear discriminant analysis	claim
66	94	Reducing forgeries in writer-independent off-line signature verification through ensemble of classifiers	claim
67	93	Shape feature extraction and description based on tensor scale	claim
68	92	Scale selection for anisotropic diffusion filter by Markov random field model	claim
69	92	Unsupervised detection and localization of structural textures using projection profiles	claim
70	89	Handwritten character recognition through two-stage foreground sub-sampling	claim
71	87	Selection-fusion approach for classification of datasets with missing values	claim
72	86	POSIT: Part-based object segmentation without intensive training	claim
73	86	Interactive imaging and vision - Ideas, algorithms and applications	claim
74	84	A new clustering algorithm for coordinate-free data	claim
75	84	Learning state machine-based string edit kernels	claim
76	83	Fixed partitioning and salient points with MPEG-7 cluster correlograms for image categorization	claim
77	82	Thermal and reflectance based personal identification methodology under variable illumination	claim
78	81	Partition-induced connections and operators for pattern analysis	claim
79	81	Hierarchical vibrations for part-based recognition of complex objects	claim
80	79	Information theoretic combination of pattern classifiers	claim
81	67	A semi-dependent decomposition approach to learn hierarchical classifiers	claim
82	65	Uncovering delayed patterns in noisy and irregularly sampled time series: An astronomy application	claim

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