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Flaw Imaging for Nondestructive Evaluation
|Contributors: ||NTOU:Department of Electrical Engineering|
Flaw imaging;Nondestructive testing;Fuzzy theory;Image reconstruction;Image enhancement
|Issue Date: ||2011-06-28T08:08:20Z
|Abstract: ||在非破壞性檢驗的應用中,由於被量測物體尺寸太大的緣故,往往無法收集到完整的180度範圍的投射資料。這類有限角度(Limited-angle)的影像重建問題,若以濾波逆投射法為之,將導致重建影像有嚴重的假象產生。一般解決此一問題,常採用由Medoff等人所提出的遞迴式重建與再投射(IRR)演算法。但因所使用的事前資訊不充分的緣故,所以重建影像的品質改善有限,而且收斂速度頗為緩慢。為了改進IRR演算法效能,我們提出以無瑕疵原型影像(Flawless prototype image)與其推演的差值限制條件的嵌入,來增加事前資訊的限制條件。再者,採用在頻率域上的限制條件,改善其收斂速度,以提昇演算法的整體效能。最後以電腦模擬的結果,來驗證所提演算法的效能。|
Because the size of the object under test is often too bulky in nondestructive evaluation, it is not possible to collect projection data over a complete angular range of 180.degree.. The image reconstruction based on filtered back-projection (FBP) , for the limited-angle problem would usually produce severe artifacts in reconstructed cross sections. The iterative reconstruction-reprojection (IRR) algorithm proposed by Medoff et al.  is commonly employed to solve the limited-angle problem. However, lack of sufficient prior information makes IRR less effective in the performance improvement of reconstructed images. Besides, the IRR algorithm has slow convergence rate in a recursive fashion to regularize the limited-angle problem. To improve the performance of the IRR algorithm, a flawless prototype image and the developed difference constraint are incorporated as additional constraints of prior information. In addition, the constraint in frequency domain  is also incorporated to increase the convergence rate. Thus the effectiveness and efficiency of the IRR algorithm can be greatly improved. Finally, computer simulation results are provided to show the effectiveness of the proposed algorithm.
|Appears in Collections:||[電機工程學系] 研究計畫|
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