Results 1 to 10 of about 8,888,697 (293)

Multi-focus image fusion using multi-scale image decomposition and saliency detection

Ain Shams Engineering Journal, 2018
In this paper, we develop a new multi-focus image fusion method based on saliency detection and multi-scale image decomposition. Proposed method is very efficient, since the visual saliency explored in this algorithm is able to emphasize visually ...
Durga Prasad Bavirisetti, Ravindra Dhuli
doaj   +3 more sources

Parameter‐adaptive nighttime image enhancement with multi‐scale decomposition

IET Computer Vision, 2016
As a challenging problem, image enhancement plays an important role in computer vision applications and has been widely studied. As one of the most difficult issues of image enhancement, outdoor nighttime image enhancement suffers from noise ...
Shuhang Wang, Jin Zheng, Bo Li
doaj   +2 more sources

Multi-Focus Color Image Fusion Based on Quaternion Multi-Scale Singular Value Decomposition

Frontiers in Neurorobotics, 2021
Most existing multi-focus color image fusion methods based on multi-scale decomposition consider three color components separately during fusion, which leads to inherent color structures change, and causes tonal distortion and blur in the fusion results.
Hui Wan, Hui Wan, Xianlun Tang, Zhiqin Zhu, Bin Xiao, Weisheng Li   +5 more
doaj   +1 more source

One Dimensional Convolutional Neural Networks Using Sparse Wavelet Decomposition for Bearing Fault Diagnosis

IEEE Access, 2022
This paper proposes a novel algorithm for bearing fault diagnosis using sparse wavelet decomposition for feature extraction combined with a multi-scale one dimensional convolutional neural network (1-D CNN).
Xiaofan Liu, Jason Centeno, Juan Alvarado, Lizhe Tan   +3 more
doaj   +1 more source

Entropy-Based Image Fusion with Joint Sparse Representation and Rolling Guidance Filter

Entropy, 2020
Image fusion is a very practical technology that can be applied in many fields, such as medicine, remote sensing and surveillance. An image fusion method using multi-scale decomposition and joint sparse representation is introduced in this paper.
Yudan Liu, Xiaomin Yang, Rongzhu Zhang, Marcelo Keese Albertini, Turgay Celik, Gwanggil Jeon   +5 more
doaj   +1 more source

GA-PE-VMD and MSE Methods for Milling Chatter Feature Extraction of Thin-walled Parts

Journal of Harbin University of Science and Technology, 2023
In the high-speed milling of aviation parts, due to the low stiffness of thin-walled structure, it is easy to produce chatter. Chatter leads to poor surface quality, dimensional error and reducing the service life of tools and machines.Therefore, a ...
WANG Hanbin, LI Maoyue, LIU Xianli, WANG Zhixue, MENG Boyang   +4 more
doaj   +1 more source

Spatio‐temporal multi‐scale motion descriptor from a spatially‐constrained decomposition for online action recognition

IET Computer Vision, 2017
This study presents a spatio‐temporal motion descriptor that is computed from a spatially‐constrained decomposition and applied to online classification and recognition of human activities.
Fabio Martínez, Antoine Manzanera, Eduardo Romero   +2 more
doaj   +1 more source

Image Fusion Method Based on Structure-Based Saliency Map and FDST-PCNN Framework

IEEE Access, 2019
Image fusion has become an active and promising research topic in image processing. It provides an effective way to combine several source images to form a composite image with more detailed information than any one of the source images.
Jiang Qian, Liu Yadong, Dai Jindun, Fu Xiaofei, Jiang Xiuchen   +4 more
doaj   +1 more source

Multi‐Scale Decomposition for Skillful All‐Season MJO Prediction With Deep Learning

Geophysical Research Letters
The Madden‐Julian Oscillation (MJO) is a key intraseasonal atmospheric pattern in the tropics, significantly influencing global weather and extreme events.
Miae Kim, Daehyun Kang, Soo‐Jin Sohn, Gayoung Kim, Jinyoung Rhee, Sunyong Kim   +5 more
doaj   +1 more source

Optimal Speech Signal Processing Based on Dynamic Multi-Scale Analysis

IEEE Access
To enhance the quality of speech signals, this paper introduces a novel speech signal processing method that integrates Dynamic Multi-Scale (DMS) and Adaptive Error Minimization (AEM) techniques.
Zefei Guo, Xiao Li, Yuchen Zhang
doaj   +1 more source