Wiener濾波器在失焦影像重整應用研討

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Title:	Wiener濾波器在失焦影像重整應用研討
Other Titles:	A studying in defocusing images with Wiener filter
Authors:	馬偉倫;Ma, Wei-Lun
Contributors:	淡江大學資訊工程學系碩士在職專班汪柏;Wang, Bal
Keywords:	失焦模糊;反卷積;點擴散函數;Wiener Filter;Point Spread Function;Defocusing;deconvolution
Date:	2016
Issue Date:	2017-08-24 23:50:59 (UTC+8)
Abstract:	論文提要內容：　　隨著目前生活中數位相機的普及，對於數位影像的處理也日益成為重要課題，但一般使用者拍攝數位影像的過程中可能不盡完美，例如拍攝時手部不穩的晃動，或是離拍攝物太過接近，而造成相機對焦失敗數位影像模糊的情況發生。因此有效地改善數位影像模糊也成為數位影像處理的主要研究方向之一。這類研究通稱為影像去模糊（Image deblur）。此類問題所產生的模糊影像可看成是相機與被拍攝物之間的晃動軌跡，或是對焦失敗造成的錯誤焦點進行卷積（Convolution）運算所產生的結果。改善這類問題的方法一般稱為反卷積（Deconvolution），常見的影像反卷積方法有Richardson-Lucy algorithm與Wiener Filter。本篇論文主要探討當影像失焦模糊發生時，使用點擴散函數（Point Spread Function）描述像素點的模糊情形，並試著找出最佳參數配合Wiener Filter以改善數位影像模糊情形。 Abstract: With the popularity of digital camera, digital image processing is getting more important. Most of photographs are not clear enough because of camera sharking, too close to the object or focus failure. So improve these blurring images are one of the major direction in image processing called “Image Deblur”. The blur process can be formulated as the image takes convolution operation with camera shaking path or focus fail. Most common deconvolve improvements are Richardson-Lucy algorithm and Wiener filter. In this paper, we use the Point Spread Function try to represent the blurring image pixels and find out an optimal parameter pair with Wiener filter to improve the image blur.
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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