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| 研究生： |
藍鈞頎 Lan, Chun-Chi. |
|---|---|
| 論文名稱： |
基於移除非常態梯度值之去模糊影像優化 Refine Deblurred Images via Removing Irregular Gradient Values |
| 指導教授： |
張隆紋
Chang, Long-Wen |
| 口試委員: |
陳朝欽
Chen, Chaur-Chin 邱瀞德 Chiu, Ching-Te |
| 學位類別： |
碩士 Master |
| 系所名稱： |
|
| 論文出版年： | 2017 |
| 畢業學年度： | 105 |
| 語文別： | 英文 |
| 論文頁數： | 37 |
| 中文關鍵詞： | 去模糊 、震鈴效應 |
| 外文關鍵詞： | deblurring, ringing |
| 相關次數： | 點閱：1 下載：0 |
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影像去模糊是一個非適定性之逆問題，因此大多的演算法會對潛在影像或模糊核做額外的假設，然而這些假設通常無法符合所有種類的影像，因此這些方法會產生如振鈴效應及過度銳利化邊緣等問題。在本篇文章中，我們提出一個新的針對影響去模糊之後處理演算法，此方法首先修改潛在影像之非常規之梯度值，接著利用修改過後之梯度值來重建出優化後之潛在影像，此方法可以有效的減少振鈴效應以及過度銳利化之邊緣。由於此方法並沒有對潛在影像做額外的假設，因此可以適用於大部分的影像類型，我們的實驗也證實此方法可以被應用到數個不同之去模糊演算法，並在大多數的影像中取得不錯的成果。
Image deblurring is an ill-posed inverse problem. Most algorithms make some assumptions of latent images or blur kernels. Since these assumptions may not suit for all kinds of images, they get some artifacts like ringing or over-sharpen edges with the images which do not fit to their assumptions. In this work, we propose a new post-processing algorithm for image deblurring. The algorithm modifies irregular values on the gradient domain of the latent image, and then reconstructs a refined image with the gradients. It can reduce ringing artifacts and over-sharpened edges effectively. The proposed algorithm does not make any assumption of latent images. That is, it can be applied to most types of images. Our experiments show that the method could be applied to several conventional image deblurring methods and get good results.
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