Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/99534
|
| Title: | 線性動態模糊影像之研究
A study of linear motion blurred image |
| Authors: | 吳諭忠
Wu, Yu Chung |
| Contributors: | 薛慧敏
Hsueh, Hui Ming
吳諭忠
Wu, Yu Chung |
| Keywords: | 線性動態模糊
影像還原
點擴散函數
旋積
傅立葉轉換
雷登轉換
Linear Motion Blur
Image Restoration
Point Spread Function
Convolution
Fourier Transform
Radon Transform |
| Date: | 2016 |
| Issue Date: | 2016-08-02 15:54:10 (UTC+8) |
| Abstract: | 生活中在使用相機時，由於機器晃動或物體移動所造成的模糊影像時常可見。當影像模糊的成因是影像曝光時間內相機與拍攝物體相對線性移動時，則我們稱為線性動態模糊。理論上，模糊影像可以表示成原始影像與點擴散函數的旋積，本文的研究重點為點擴散函數中模糊參數的估計，雷登轉換將被運用在此問題上。我們首先介紹兩個現有方法，我們將探討這些方法中用來消除雜訊的步驟之適用性及必要性。另一方面，在模糊參數的估計過程中，我們在雷登轉換加入圓限制以及採用移動平均法。我們透過實驗證實，本篇提出的方法可以獲得更準確的估計結果以及更好的模糊影像還原效果。
Nowadays, collecting a digital image becomes convenient and low-cost due to rapid progress in digital camera technology. Blurred images frequently appear because of camera shake or moving objects. There are several different types of blur. When the blur is caused by the linear motion between the object and the camera during the light exposure, it’s called a linear motion blur. Mathematically, a blurred image is expressed as a convolution of a point spread function and the original image. Our study considers Radon transform for the estimation of the point spread function. To improve the existing methods, a circle restriction and the moving average method are applied in the estimating procedure. Through intensive experiments, the proposed method is found enable to produce more accurate estimation and better performance in image restoration. |
| Reference: | Bracewell, R. N.(2000) The Fourier Transform and Its Applications (3rd ed.), Boston: McGraw-Hill, ISBN 0-07-116043-4.
Dobes ̆, M. , Machala, L. and Fu ̈rst, T. (2010) Blurred Image Restoration: A Fast Method Of Finding The Motion Length And Angle, Digital Signal Processing, vol. 20, no. 6, pp. 1677-1686.
Dutta,A. , Dhar,A. and Nandy, k. (2010) Image Deconvolution By Richardson Lucy Algorithm, Indina Statistical Institute, November 2010.
Fiche,C. , Ladret,P. and Vu, N.-S. (2010) Blurred Face Recognition Algorithm Guided By A No-reference Blur Metric. Proceedings of SPIE, The International Society for Optical Engineering, 7538.
Lagendijk,R. L.and Biemond,J. (1999) Basic Methods For Image Restoration And Identifcation, International Conference on Image and Graphics.
Lokhande,R. , Arya,K. V. and Gupta,p. (2006) Identification Of Blur Parameters and Restoration Of Motion Blurred Images, in Proc. ACM Symposium on Applied Computing, pp. 301-305.
Nguyen, D. T., Cho, S. R., Pham, T. D. and Park, K. R. (2015) Human Age Estimation Method Robust To Camera Sensor And/or Face Movement, Sensors 2015, 15, 21898-21930.
Richardson, W. H. (1972) Bayesian-Based Iterative Method Of Image Restoration JOSA 62.1,pp. 55-59.
Tiwari, S. , Shukla, V. P. and Singh, A. K. (2013) Review Of Motion Blur Estimation Techniques, Journal of Image and Graphics vol. 1, No.4 |
| Description: | 碩士
國立政治大學
統計學系
103354026 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0103354026 |
| Data Type: | thesis |
| Appears in Collections: | [統計學系] 學位論文
|
Files in This Item:
| File |
Size | Format | |
|---|
| 402601.pdf | 6987Kb | Adobe PDF2 | 222 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
