Results 21 to 30 of about 64,008 (285)
IET Image Processing, 2021 Fusion and noise suppression of medical images are becoming increasingly difficult to be ignored in image processing, and this technique provides abundant information for the clinical diagnosis and treatment.
Xuefeng Zhang, Hui Yan
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Multi-Exposure Image Fusion Algorithm Based on Improved Weight Function
Frontiers in Neurorobotics, 2022 High-dynamic-range (HDR) image has a wide range of applications, but its access is limited. Multi-exposure image fusion techniques have been widely concerned because they can obtain images similar to HDR images. In order to solve the detail loss of multi-
Ke Xu +3 more
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FSADFuse: A Novel Fusion Approach to Infrared and Visible Images
IEEE Access, 2021 To address the problems of edge blur and weak detail resolution when fusing infrared and visible images with traditional methods, a novel image fusion approach based on fast super-resolution convolutional neural network and anisotropic diffusion is ...
Shuai Hao +5 more
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The Study of Feature Extraction Method Based on Multi-scale Morphological Spectrum Entropy
Chemical Engineering Transactions, 2016 Multi-scale morphological decomposition is a decomposition method being proposed based on the basic theory of multi-scale morphology. Using from small to large scale of structural elements to deal with different “Scale domain”, thus the original signal ...
H.M. Ge, L. Chen, J. Liang
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Deep Residual Transform for Multi-scale Image Decomposition
Journal of Computational Vision and Imaging Systems, 2021 Multi-scale image decomposition (MID) is a fundamental task in computer vision and image processing that involves the transformation of an image into a hierarchical representation comprising of different levels of visual granularity from coarse structures to fine details.
Linlin Xu +4 more
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A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Many real-world time series exhibit multiple seasonality with different lengths. The removal of seasonal components is crucial in numerous applications of time series, including forecasting and anomaly detection. However, many seasonal-trend decomposition algorithms suffer from high computational cost and require a large amount of data when multiple ...
Yang, Linxiao +3 more
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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 +4 more
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Multi-scale Image Decomposition Using a Local Statistical Edge Model [PDF]
2021 IEEE 7th International Conference on Virtual Reality (ICVR), 2021 We present a progressive image decomposition method based on a novel non-linear filter named Sub-window Variance filter. Our method is specifically designed for image detail enhancement purpose; this application requires extraction of image details which are small in terms of both spatial and variation scales.
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Systematic multi-scale decomposition of ocean variability using machine learning
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 Multi-scale systems, such as the climate system, the atmosphere, and the ocean, are hard to understand and predict due to their intrinsic nonlinearities and chaotic behavior. Here, we apply a physics-consistent machine learning method, the multi-resolution dynamic mode decomposition (mrDMD), to oceanographic data.
Christian L. E. Franzke +2 more
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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
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