Multi-focus image fusion: A survey of the state of the art
Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …
lenses by creating an all-in-focus image from a set of partially focused images of the same …
Multivariate variational mode decomposition
N ur Rehman, H Aftab - IEEE Transactions on signal …, 2019 - ieeexplore.ieee.org
We present a generic extension of variational mode decomposition (VMD) algorithm to
multivariate or multichannel data. The proposed method utilizes a model for multivariate …
multivariate or multichannel data. The proposed method utilizes a model for multivariate …
Review of various image fusion algorithms and image fusion performance metric
Image fusion is the process in which substantial information taken through different sensors,
different exposure values and at different focus points is integrated together to generate a …
different exposure values and at different focus points is integrated together to generate a …
Image fusion with guided filtering
A fast and effective image fusion method is proposed for creating a highly informative fused
image through merging multiple images. The proposed method is based on a two-scale …
image through merging multiple images. The proposed method is based on a two-scale …
A combination forecasting model based on hybrid interval multi-scale decomposition: Application to interval-valued carbon price forecasting
J Liu, P Wang, H Chen, J Zhu - Expert Systems with Applications, 2022 - Elsevier
Forecasting carbon price accurately is of great significance to ensure the healthy
development of the carbon market. However, due to the non-linearity, non-stationarity, and …
development of the carbon market. However, due to the non-linearity, non-stationarity, and …
Multivariate empirical mode decomposition
Despite empirical mode decomposition (EMD) becoming a de facto standard for time-
frequency analysis of nonlinear and non-stationary signals, its multivariate extensions are …
frequency analysis of nonlinear and non-stationary signals, its multivariate extensions are …
Fusion of infrared and visible sensor images based on anisotropic diffusion and Karhunen-Loeve transform
DP Bavirisetti, R Dhuli - IEEE Sensors Journal, 2015 - ieeexplore.ieee.org
Image fusion is a process of generating a more informative image from a set of source
images. Major applications of image fusion are in navigation and military. Here, infrared and …
images. Major applications of image fusion are in navigation and military. Here, infrared and …
Empirical mode decomposition-based time-frequency analysis of multivariate signals: The power of adaptive data analysis
This article addresses data-driven time-frequency (TF) analysis of multivariate signals, which
is achieved through the empirical mode decomposition (EMD) algorithm and its noise …
is achieved through the empirical mode decomposition (EMD) algorithm and its noise …
Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation
Solar energy is an alternative renewable energy resource that has the potential of cleanly
addressing the increasing demand for electricity in the modern era to overcome future …
addressing the increasing demand for electricity in the modern era to overcome future …
Filter bank property of multivariate empirical mode decomposition
N Ur Rehman, DP Mandic - IEEE transactions on signal …, 2011 - ieeexplore.ieee.org
The multivariate empirical mode decomposition (MEMD) algorithm has been recently
proposed in order to make empirical mode decomposition (EMD) suitable for processing of …
proposed in order to make empirical mode decomposition (EMD) suitable for processing of …