Video denoising via empirical bayesian estimation of space-time patches
P Arias, JM Morel - Journal of Mathematical Imaging and Vision, 2018 - Springer
In this paper we present a new patch-based empirical Bayesian video denoising algorithm.
The method builds a Bayesian model for each group of similar space-time patches. These …
The method builds a Bayesian model for each group of similar space-time patches. These …
The sample complexity of dictionary learning
D Vainsencher, S Mannor… - Proceedings of the 24th …, 2011 - proceedings.mlr.press
A large set of signals can sometimes be described sparsely using a dictionary, that is, every
element can be represented as a linear combination of few elements from the dictionary …
element can be represented as a linear combination of few elements from the dictionary …
Entropy based dictionary learning for image classification
In this paper, a new discriminative dictionary learning algorithm is introduced. An entropy
based criterion is embedded into the objective function to enforce a proper structure for the …
based criterion is embedded into the objective function to enforce a proper structure for the …
Unified single-image and video super-resolution via denoising algorithms
Single image super-resolution (SISR) aims to recover a high-resolution image from a given
low-resolution version of it. Video super-resolution (VSR) targets a series of given images …
low-resolution version of it. Video super-resolution (VSR) targets a series of given images …
Image and video denoising using adaptive dual-tree discrete wavelet packets
We investigate image and video denoising using adaptive dual-tree discrete wavelet
packets (ADDWP), which is extended from the dual-tree discrete wavelet transform (DDWT) …
packets (ADDWP), which is extended from the dual-tree discrete wavelet transform (DDWT) …
Robust Kronecker product video denoising based on fractional-order total variation model
G Chen, J Zhang, D Li, H Chen - Signal Processing, 2016 - Elsevier
Most existing sparse representation-based video denoising algorithms assume video noise
is additive Gaussian white noise, which is often violated in practice. In this paper, a robust …
is additive Gaussian white noise, which is often violated in practice. In this paper, a robust …
Towards a bayesian video denoising method
P Arias, JM Morel - Advanced Concepts for Intelligent Vision Systems: 16th …, 2015 - Springer
The quality provided by image and video sensors increases steadily, and for a fixed spatial
resolution the sensor noise has been gradually reduced over the years. However, modern …
resolution the sensor noise has been gradually reduced over the years. However, modern …
Nonlocal video denoising, simplification and inpainting using discrete regularization on graphs
M Ghoniem, Y Chahir, A Elmoataz - Signal Processing, 2010 - Elsevier
We present nonlocal algorithms for video denoising, simplification and inpainting based on
a generic framework of discrete regularization on graphs. We express video denoising …
a generic framework of discrete regularization on graphs. We express video denoising …
Measuring noise correlation for improved video denoising
The vast majority of previous work in noise reduction for visual media has assumed
uncorrelated, white, noise sources. In practice this is almost always violated by real media …
uncorrelated, white, noise sources. In practice this is almost always violated by real media …
Dictionary learning enhancement framework: Learning a non-linear mapping model to enhance discriminative dictionary learning methods
In this paper, a new framework is presented to enhance the reconstruction and
discrimination capabilities of existing discriminative dictionary learning methods. In the …
discrimination capabilities of existing discriminative dictionary learning methods. In the …