Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/136966| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 彭彥璁 | zh_TW |
| dc.contributor.advisor | Peng, Yan-Tsung | en_US |
| dc.contributor.author | 黃莎涴 | zh_TW |
| dc.contributor.author | Sha-Wan Huang | en_US |
| dc.creator | 黃莎涴 | zh_TW |
| dc.creator | Huang, Sha-Wan | en_US |
| dc.date | 2021 | en_US |
| dc.date.accessioned | 2021-09-02T08:55:51Z | - |
| dc.date.available | 2021-09-02T08:55:51Z | - |
| dc.date.issued | 2021-09-02T08:55:51Z | - |
| dc.identifier | G0108753138 | en_US |
| dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/136966 | - |
| dc.description | 碩士 | zh_TW |
| dc.description | 國立政治大學 | zh_TW |
| dc.description | 資訊科學系 | zh_TW |
| dc.description | 108753138 | zh_TW |
| dc.description.abstract | 高動態範圍 (HDR) 成像需要融合在同一場景中以多種不同曝光程度的影像以覆蓋整個動態範圍。以目前現有的研究中，只利用少數低動態範圍 (LDR) 影像，這仍然是一項具有挑戰性的任務。本論文提出了一種新穎的兩曝光影像融合模型，此模型具有我們提出的交叉注意力融合模組 (CAFM)，可使用一個影像的高曝光的部分來補償因曝光不足或過度曝光而導致的另一張影像內容缺失的部分。CAFM 由 交叉注意力融合(Cross Attention Fusion) 和 通道注意力融合(Channel Attention Fusion) 組成，以實現雙分支融合，從而產生出色的融合結果。並且在公開的HDR 資料集上，我們進行大量實驗以證明所提出的模型在與最先驅的圖像融合方法比較時表現良好。 | zh_TW |
| dc.description.abstract | High Dynamic Range (HDR) imaging requires the fusion of images captured with multiple exposure ratios in the same scene to cover the entire dynamic range. With only a few low dynamic range (LDR) images, it remains a challenging task. The paper presents a novel two-exposure image fusion model that features the proposed Cross Attention Fusion Module (CAFM) to use one image`s highlight to compensate for the other`s content loss caused by under-exposure or over-exposure. The CAFM consists of Cross Attention Fusion and Channel Attention Fusion to achieve a dual-branch fusion for producing superior fusion results. The extensive experimental results on benchmark HDR public datasets demonstrate that the proposed model performs favorably against the state-of-the-art image fusion methods. | en_US |
| dc.description.tableofcontents | 論文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I\nAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I\n目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III\n圖目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V\n表目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII\n1緒論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1\n1.1研究背景與動機. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1\n1.2研究目的. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2\n1.3論文架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3\n2技術背景與相關研究. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4\n2.1基於傳統影像處理的HDR影像融合. . . . . . . . . . . . . . . . . . . . 4\n2.2基於深度學習方式的HDR影像融合. . . . . . . . . . . . . . . . . . . . 6\n2.3注意力機制技術介紹與進展. . . . . . . . . . . . . . . . . . . . . . . . . 11\n2.4小結. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14\n3研究方法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16\n3.1高動態範圍影像生成. . . . . . . . . . . . . . . . . . . . . . . . . . . . 16\n3.1.1條狀池化注意力機制介紹(Strip Pooling Attention) . . . . . . . . 17\n3.1.2交叉注意力融合(Cross Attention Fusion, XAF) . . . . . . . . . . 18\n3.1.3通道注意力融合(Channel Attention Fusion, CAF) . . . . . . . . 20\n3.2損失函數. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20\n3.2.1損失函數. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21\n3.3資料集. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21\n3.4訓練設置. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22\n3.5融合評估指標. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22\n4實驗結果與分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25\n5消融研究. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30\n6結論與後續工作. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32\n參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 | zh_TW |
| dc.format.extent | 8999798 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri | http://thesis.lib.nccu.edu.tw/record/#G0108753138 | en_US |
| dc.subject | 高動態範圍成像 | zh_TW |
| dc.subject | 兩曝光影像融合 | zh_TW |
| dc.subject | High Dynamic Range imaging | en_US |
| dc.subject | Two-exposure image fusion | en_US |
| dc.title | 基於交叉注意力合成之二曝光影像融合 | zh_TW |
| dc.title | TwoExposure Image Fusion based on Cross Attention Fusion | en_US |
| dc.type | thesis | en_US |
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| dc.identifier.doi | 10.6814/NCCU202101538 | en_US |
| item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
| item.fulltext | With Fulltext | - |
| item.cerifentitytype | Publications | - |
| item.grantfulltext | restricted | - |
| item.openairetype | thesis | - |
| Appears in Collections: | 學位論文 | |
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