Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Biased anisotropic diffusion: a unified regularization and diffusion approach to edge detection
Image and Vision Computing - Special issue on the first ECCV 1990
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Fields of Experts: A Framework for Learning Image Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Unsupervised, Information-Theoretic, Adaptive Image Filtering for Image Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Unsupervised texture segmentation with nonparametric neighborhood statistics
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency
IEEE Transactions on Signal Processing
Inferring the eigenvalues of covariance matrices from limited,noisy data
IEEE Transactions on Signal Processing
A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising
IEEE Transactions on Image Processing
The curvelet transform for image denoising
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
Optimal Spatial Adaptation for Patch-Based Image Denoising
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Efficient Nonlocal Means for Denoising of Textural Patterns
IEEE Transactions on Image Processing
Non local image denoising using image adapted neighborhoods
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
A general system for automatic biomedical image segmentation using intensity neighborhoods
Journal of Biomedical Imaging
Image denoising using bilateral filter in high dimensional PCA-space
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Patch reprojections for Non-Local methods
Signal Processing
Non-local adaptive structure tensors
Image and Vision Computing
A Bias-Variance Approach for the Nonlocal Means
SIAM Journal on Imaging Sciences
Pattern Recognition Letters
An MMSE approach to nonlocal image denoising: Theory and practical implementation
Journal of Visual Communication and Image Representation
A multiresolution framework for local similarity based image denoising
Pattern Recognition
Time-Scale Similarities for Robust Image De-noising
Journal of Mathematical Imaging and Vision
Structure guided fusion for depth map inpainting
Pattern Recognition Letters
Image denoising via 2D dictionary learning and adaptive hard thresholding
Pattern Recognition Letters
Joint image denoising using adaptive principal component analysis and self-similarity
Information Sciences: an International Journal
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We present an in-depth analysis of a variation of the nonlocal means (NLM) image denoising algorithm that uses principal component analysis (PCA) to achieve a higher accuracy while reducing computational load. Image neighborhood vectors are first projected onto a lower dimensional subspace using PCA. The dimensionality of this subspace is chosen automatically using parallel analysis. Consequently, neighborhood similarity weights for denoising are computed using distances in this subspace rather than the full space. The resulting algorithm is referred to as principal neighborhood dictionary (PND) nonlocal means. We investigate PND's accuracy as a function of the dimensionality of the projection subspace and demonstrate that denoising accuracy peaks at a relatively low number of dimensions. The accuracy of NLM and PND are also examined with respect to the choice of image neighborhood and search window sizes. Finally, we present a quantitative and qualitative comparison of PND versus NLM and another image neighborhood PCA-based state-of-the-art image denoising algorithm.