The quest for identifiability in human functional connectomes
The evaluation of the individual “fingerprint” of a human functional connectome (FC) is
becoming a promising avenue for neuroscientific research, due to its enormous potential …
becoming a promising avenue for neuroscientific research, due to its enormous potential …
Hyperspectral image denoising using local low-rank matrix recovery and global spatial–spectral total variation
Hyperspectral images (HSIs) are usually contaminated by various kinds of noise, such as
stripes, deadlines, impulse noise, Gaussian noise, and so on, which significantly limits their …
stripes, deadlines, impulse noise, Gaussian noise, and so on, which significantly limits their …
A nonlocal Bayesian image denoising algorithm
Recent state-of-the-art image denoising methods use nonparametric estimation processes
for 8*8 patches and obtain surprisingly good denoising results. The mathematical and …
for 8*8 patches and obtain surprisingly good denoising results. The mathematical and …
Sparse representation based image interpolation with nonlocal autoregressive modeling
Sparse representation is proven to be a promising approach to image super-resolution,
where the low-resolution (LR) image is usually modeled as the down-sampled version of its …
where the low-resolution (LR) image is usually modeled as the down-sampled version of its …
Image fusion using hybrid methods in multimodality medical images
An image fusion based on multimodal medical images renders a considerable
enhancement in the quality of fused images. An effective image fusion technique produces …
enhancement in the quality of fused images. An effective image fusion technique produces …
Image denoising using the higher order singular value decomposition
A Rajwade, A Rangarajan… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
In this paper, we propose a very simple and elegant patch-based, machine learning
technique for image denoising using the higher order singular value decomposition …
technique for image denoising using the higher order singular value decomposition …
Poisson noise reduction with non-local PCA
J Salmon, Z Harmany, CA Deledalle… - Journal of mathematical …, 2014 - Springer
Photon-limited imaging arises when the number of photons collected by a sensor array is
small relative to the number of detector elements. Photon limitations are an important …
small relative to the number of detector elements. Photon limitations are an important …
Low-rank quaternion approximation for color image processing
Low-rank matrix approximation (LRMA)-based methods have made a great success for
grayscale image processing. When handling color images, LRMA either restores each color …
grayscale image processing. When handling color images, LRMA either restores each color …
Image restoration using joint patch-group-based sparse representation
Sparse representation has achieved great success in various image processing and
computer vision tasks. For image processing, typical patch-based sparse representation …
computer vision tasks. For image processing, typical patch-based sparse representation …
BM3D-Net: A convolutional neural network for transform-domain collaborative filtering
D Yang, J Sun - IEEE Signal Processing Letters, 2017 - ieeexplore.ieee.org
Denoising is a fundamental task in image processing with wide applications for enhancing
image qualities. BM3D is considered as an effective baseline for image denoising. Although …
image qualities. BM3D is considered as an effective baseline for image denoising. Although …