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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/138324

Title:	Image Denoising Using Adaptive and Overlapped Average Filtering and Mixed-Pooling Attention Refinement Networks
Authors:	彭彥璁 Peng, Yan-Tsung Lin, Ming-Hao Hou, Zhi-Xiang Cheng, Kai-Han Wu, Chin-Hsien
Contributors:	資科系
Keywords:	image denoising; overlapped averaging; mixed-pooling attention
Date:	2021-05
Issue Date:	2021-12-23 15:41:09 (UTC+8)
Abstract:	Cameras are essential parts of portable devices, such as smartphones and tablets. Most people have a smartphone and can take pictures anywhere and anytime to record their lives. However, these pictures captured by cameras may suffer from noise contamination, causing issues for subsequent image analysis, such as image recognition, object tracking, and classification of an object in the image. This paper develops an effective combinational denoising framework based on the proposed Adaptive and Overlapped Average Filtering (AOAF) and Mixed-pooling Attention Refinement Networks (MARNs). First, we apply AOAF to the noisy input image to obtain a preliminarily denoised result, where noisy pixels are removed and recovered. Next, MARNs take the preliminary result as the input and output a refined image where details and edges are better reconstructed. The experimental results demonstrate that our method performs favorably against state-of-the-art denoising methods.
Relation:	Mathematics, pp.1130
Data Type:	article
DOI 連結:	https://doi.org/10.3390/math9101130
DOI:	10.3390/math9101130
Appears in Collections:	[資訊科學系] 期刊論文

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