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Multi-Focus Image Fusion Method Based on Multi-Scale Decomposition of Information Complementary [PDF]
Entropy, 2021 Multi-focus image fusion is an important method used to combine the focused parts from source multi-focus images into a single full-focus image. Currently, to address the problem of multi-focus image fusion, the key is on how to accurately detect the ...
Hui Wan +3 more
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IEEE Access, 2017 Image fusion is a well-recognized and a conventional field of image processing. Image fusion provides an efficient way of enhancing and combining pixel-level data resulting in highly informative data for human perception as compared with individual input
Ayush Dogra, Bhawna Goyal, Sunil Agrawal
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AMDCnet: attention-gate-based multi-scale decomposition and collaboration network for long-term time series forecasting [PDF]
Frontiers in Artificial IntelligenceIntroductionTime series analysis plays a critical role in various applications, including sensor data monitoring, weather forecasting, economic predictions, and network traffic management. While traditional methods primarily focus on modeling time series
Shikang Hou +4 more
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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
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Journal of Marine Science and Engineering, 2023 Visual object detection is an essential task for the intelligent navigation of an Unmanned Surface Vehicle (USV), which can sense the obstacles while navigating.
Zhiguo Zhou +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 ...
Linxiao Yang +3 more
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IEEE Access, 2021 Numerous studies employ multi-scale decomposition to improve the prediction performance of neural networks, but the grounds for selecting the decomposition algorithm are not explained, and the effects of decomposition algorithms on other performance of ...
Haichao Huang +4 more
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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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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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