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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
TLDR
This paper investigates the construction of feed-forward denoising convolutional neural networks (DnCNNs) to embrace the progress in very deep architecture, learning algorithm, and regularization method into image Denoising, and uses residual learning and batch normalization to speed up the training process as well as boost theDenoising performance. Expand
FSIM: A Feature Similarity Index for Image Quality Assessment
TLDR
A novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features. Expand
Sparse representation or collaborative representation: Which helps face recognition?
TLDR
This paper indicates that it is the CR but not the l1-norm sparsity that makes SRC powerful for face classification, and proposes a very simple yet much more efficient face classification scheme, namely CR based classification with regularized least square (CRC_RLS). Expand
A Completed Modeling of Local Binary Pattern Operator for Texture Classification
TLDR
It is shown that CLBP_S preserves more information of the local structure thanCLBP_M, which explains why the simple LBP operator can extract the texture features reasonably well and can be made for rotation invariant texture classification. Expand
Weighted Nuclear Norm Minimization with Application to Image Denoising
TLDR
Experimental results clearly show that the proposed WNNM algorithm outperforms many state-of-the-art denoising algorithms such as BM3D in terms of both quantitative measure and visual perception quality. Expand
Fisher Discrimination Dictionary Learning for sparse representation
TLDR
A novel dictionary learning (DL) method based on the Fisher discrimination criterion, whose dictionary atoms have correspondence to the class labels is learned so that the reconstruction error after sparse coding can be used for pattern classification. Expand
Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index
TLDR
It is found that the pixel-wise gradient magnitude similarity (GMS) between the reference and distorted images combined with a novel pooling strategy-the standard deviation of the GMS map-can predict accurately perceptual image quality. Expand
Real-Time Compressive Tracking
TLDR
A simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from the multi-scale image feature space with data-independent basis that performs favorably against state-of-the-art algorithms on challenging sequences in terms of efficiency, accuracy and robustness. Expand
FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising
TLDR
The proposed FFDNet works on downsampled sub-images, achieving a good trade-off between inference speed and denoising performance, and enjoys several desirable properties, including the ability to handle a wide range of noise levels effectively with a single network. Expand
Nonlocally Centralized Sparse Representation for Image Restoration
TLDR
The so-called nonlocally centralized sparse representation (NCSR) model is as simple as the standard sparse representation model, and the extensive experiments validate the generality and state-of-the-art performance of the proposed NCSR algorithm. Expand
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