WEKO3
アイテム
Fast Guided Median Filter
https://repository.lib.tottori-u.ac.jp/records/2001632
https://repository.lib.tottori-u.ac.jp/records/200163266b79c58-5f50-4666-90a1-082267e71ee0
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
ieeetip32_737.pdf (13.8 MB)
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| Item type | デフォルトアイテムタイプ（フル）(1) | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2025-01-22 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Fast Guided Median Filter | |||||||||||
| 言語 | en | |||||||||||
| 作成者 |
三柴,数
× 三柴,数
WEKO
04728
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| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Weighted median filter | |||||||||||
| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | guided filter | |||||||||||
| 内容記述 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | Faster computation of a weighted median (WM) filter is impeded by the construction of a weighted histogram for every local window of data. Since the calculated weights vary for each local window, it is difficult, using a sliding window approach, to construct the weighted histogram efficiently. In this paper, we propose a novel WM filter that overcomes the difficulty of histogram construction. Our proposed method achieves real-time processing for higher resolution images and can be applied to multidimensional, multichannel, and high precision data. The weight kernel used in our WM filter is the pointwise guided filter, which is derived from the guided filter. The use of kernels based on the guided filter avoids gradient reversal artifacts and shows a higher denoising performance than the Gaussian kernel based on the color/intensity distance. The core idea of the proposed method is a formulation that allows the use of histogram updates with a sliding window approach to find the weighted median. For high precision data we propose an algorithm based on a linked list that can reduce the memory requirements of storing histograms and the computational cost of updating them. We present implementations of the proposed method that are suitable for both CPU and GPU. Experimental results show that the proposed method indeed realizes faster computation than conventional WM filters and is capable of filtering multidimensional, multichannel, and high precision data. This is an approach which is difficult to achieve with conventional methods. | |||||||||||
| 言語 | en | |||||||||||
| 出版者 | ||||||||||||
| 出版者 | Institute of Electrical and Electronics Engineers (IEEE) | |||||||||||
| 言語 | en | |||||||||||
| 日付 | ||||||||||||
| 日付 | 2023-01-05 | |||||||||||
| 日付タイプ | Issued | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
| 資源タイプ | journal article | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | VoR | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
| 関連情報 | ||||||||||||
| 関連タイプ | isIdenticalTo | |||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.1109/tip.2022.3232916 | |||||||||||
| 収録物識別子 | ||||||||||||
| 収録物識別子タイプ | PISSN | |||||||||||
| 収録物識別子 | 19410042 | |||||||||||
| 収録物名 | ||||||||||||
| 収録物名 | IEEE Transactions on Image Processing | |||||||||||
| 言語 | en | |||||||||||
| 巻 | ||||||||||||
| 巻 | 32 | |||||||||||
| ページ数 | ||||||||||||
| ページ数 | 13 | |||||||||||
| 開始ページ | ||||||||||||
| 開始ページ | 737 | |||||||||||
| 終了ページ | ||||||||||||
| 終了ページ | 749 | |||||||||||
| 書誌情報 |
en : IEEE Transactions on Image Processing 巻 32, p. 737-749, ページ数 13, 発行日 2023-01-05 |
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| アクセス権 | ||||||||||||
| アクセス権 | open access | |||||||||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||||||
| 権利情報 | ||||||||||||
| 言語 | en | |||||||||||
| 権利情報 | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ | |||||||||||
