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    Please use this identifier to cite or link to this item: http://ccur.lib.ccu.edu.tw/handle/A095B0000Q/410

    Title: 基於四元樹切割和聚焦分析之多聚焦影像融合;Multi-focus image fusion based on quadtree segmentation and focus analysis
    Authors: 施惟中;Shih, Wei-Jhong
    Contributors: 電機工程研究所
    Keywords: 四元樹;多聚焦影像融合;深度圖;quadtree;All-focus;multi-focus;image fusion;depth image
    Date: 2017
    Issue Date: 2019-07-17
    Publisher: 電機工程研究所
    Abstract: 隨著科技的發展,數位相機除了扮演著重要角色,其性能也有顯著的提升。然而,在拍攝影像期間有著眾多因素會影響影像清晰度,例如:焦距、光圈、鏡頭的種類……等等。因此,我們常藉著拍攝多張影像,各自取出每一張影像有對焦 (in focus)的區域再將其融合為一張全聚焦 (all in focus)影像。本論文提出一個全聚焦影像合成的演算法,係以四元樹 (quadtree)分割為基礎,共分為兩大部分,第一部分為前處理,藉由計算各個子區塊峰度 (Kurtosis)來得到初始的融合影像以及初始深度圖;第二部分為後處理,用來修正初始深度圖上的錯誤深度,再利用修改過後的深度圖優化初始的融合影像。根據實驗結果,本論文提出的演算法所產生出的合成影像有不錯的品質。此外,本論文共用了四種客觀品質評估指標來評斷融合影像的品質。其結果顯示本論文提出的演算法所產生之融合影像在四個評估指標下,大部分是優於市售軟體的。
    When we take pictures, there are so many factor may influence the clarity of photos such as aperture and shutter. In this paper, we concern about doing multi-focus image fusion based on quadtree segmentation. The multi-focus image sets are captured by adjusting the positions of the imaging plane step by step. In this way, the objects at different depths will have their best focus at different images. Our target is to get the all-focus image and estimate the corresponding depth image for this multi-focus image set. First, we utilize kurtosis to determine whether a block should be subject to further splitting. After all the blocks are segmented completely, the final region definitions are used to perform WTA (Winner-take-all) for choosing image pixels of best focus from the image set. Depth image then corresponds to the label image by which image pixels of best focus are chosen. At last, the experimental results show that the algorithm we proposed has better performances compared to commercial software.
    Appears in Collections:[電機工程研究所] 學位論文

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