Bayesian retinex underwater image enhancement

P Zhuang, C Li, J Wu - Engineering Applications of Artificial Intelligence, 2021‏ - Elsevier
This paper develops a Bayesian retinex algorithm for enhancing single underwater image
with multiorder gradient priors of reflectance and illumination. First, a simple yet effective …

Solving constrained total-variation image restoration and reconstruction problems via alternating direction methods

MK Ng, P Weiss, X Yuan - SIAM journal on Scientific Computing, 2010‏ - SIAM
In this paper, we study alternating direction methods for solving constrained total-variation
image restoration and reconstruction problems. Alternating direction methods can be …

Constrained total variation deblurring models and fast algorithms based on alternating direction method of multipliers

RH Chan, M Tao, X Yuan - SIAM Journal on imaging Sciences, 2013‏ - SIAM
The total variation (TV) model is attractive in that it is able to preserve sharp attributes in
images. However, the restored images from TV-based methods do not usually stay in a …

Survey on sparsity in geometric modeling and processing

L Xu, R Wang, J Zhang, Z Yang, J Deng, F Chen, L Liu - Graphical Models, 2015‏ - Elsevier
Techniques from sparse representation have been successfully applied in many areas like
digital image processing, computer vision and pattern recognition in the past ten years …

A fast algorithm for Euler's elastica model using augmented Lagrangian method

XC Tai, J Hahn, GJ Chung - SIAM Journal on Imaging Sciences, 2011‏ - SIAM
Minimization of functionals related to Euler's elastica energy has a wide range of
applications in computer vision and image processing. A high order nonlinear partial …

Develop then rival: A human vision-inspired framework for superimposed image decomposition

H Duan, W Shen, X Min, Y Tian, JH Jung… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
A single superimposed image containing two image views causes visual confusion for both
human vision and computer vision. Human vision needs a “develop-then-rival” process to …

Accelerating ADMM for efficient simulation and optimization

J Zhang, Y Peng, W Ouyang, B Deng - ACM Transactions on Graphics …, 2019‏ - dl.acm.org
The alternating direction method of multipliers (ADMM) is a popular approach for solving
optimization problems that are potentially non-smooth and with hard constraints. It has been …

Primal–dual methods for large-scale and distributed convex optimization and data analytics

D Jakovetić, D Bajović, J Xavier… - Proceedings of the …, 2020‏ - ieeexplore.ieee.org
The augmented Lagrangian method (ALM) is a classical optimization tool that solves a given
“difficult”(constrained) problem via finding solutions of a sequence of “easier”(often …

Convex image denoising via non-convex regularization with parameter selection

A Lanza, S Morigi, F Sgallari - Journal of Mathematical Imaging and Vision, 2016‏ - Springer
We introduce a convex non-convex (CNC) denoising variational model for restoring images
corrupted by additive white Gaussian noise. We propose the use of parameterized non …

Adaptive directional total-variation model for latent fingerprint segmentation

J Zhang, R Lai, CCJ Kuo - IEEE Transactions on Information …, 2013‏ - ieeexplore.ieee.org
A new image decomposition scheme, called the adaptive directional total variation (ADTV)
model, is proposed to achieve effective segmentation and enhancement for latent fingerprint …