Adaptive kernel-based image denoising employing semi-parametric regularization

IEEE Transactions on Image Processing

Volumn 19, Issue 6, 2010, Pages 1465-1479

  Bouboulis, Pantelis ^a   Slavakis, Konstantinos ^b   Theodoridis, Sergios ^a  

^a UNIVERSITY OF ATHENS   (Greece)

^b UNIVERSITY OF PELOPONNESE   (Greece)

Author keywords

Denoising; Kernel; Reproducing Kernel Hilbert Spaces (RKHS); Semi parametric representer theorem

Indexed keywords

ADAPTIVE KERNELS; DE-NOISING; DE-NOISING TECHNIQUES; DIGITAL IMAGE; EDGE PRESERVATIONS; GAUSSIAN NOISE; GAUSSIANS; IMAGE DE-NOISING; MIXED NOISE; NOISE REMOVAL; OPTIMIZATION TASK; REPRESENTER THEOREM; REPRODUCING KERNEL HILBERT SPACES; SEMIPARAMETRIC; SPATIAL DOMAINS;

IMAGE PROCESSING; WAVELET ANALYSIS;

HILBERT SPACES;

ALGORITHM; ARTICLE; ARTIFACT; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; ARTIFACTS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 77952590168     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2010.2042995     Document Type: Article

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