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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73530完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅楸善 | |
| dc.contributor.author | Chih-Jou Yang | en |
| dc.contributor.author | 楊至柔 | zh_TW |
| dc.date.accessioned | 2021-06-17T07:40:15Z | - |
| dc.date.available | 2022-02-20 | |
| dc.date.copyright | 2019-02-20 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-02-15 | |
| dc.identifier.citation | [1] A. Buades, B. Coll, and J. M. Morel, “A Non-Local Algorithm for Image Denoising,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, San Diego, CA, pp. 1-6, 2005.
[2] A. Darmont, J. Chahiba, J. F. Lemaitre, M. Pirson, and D. Dethier, “Implementing and Using the EMVA1288 Standard,” http://adsabs.harvard.edu/abs/2012SPIE.8298E..0HD, 2012. [3] European Machine Vision Association. “EMVA Standard 1288 Release 3.1,” http://www.emva.org/wp-content/uploads/EMVA1288-3.1a.pdf, 2016. [4] C. Tomasi and R. Manduchi, “Bilateral Filtering for Gray and Color Images,” Proceedings of International Conference on Computer Vision, Bombay, India, pp. 839-846, 1998. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73530 | - |
| dc.description.abstract | 本論文提出一個對於歐洲電腦視覺協會(EMVA1288)檢測標準之下的影像品質改善方法，首先根據EMVA1288作為標準對影像感測器的包含雜訊的各種感測器特性以及品質做分析，對於檢測影像感測器所使用的實驗設定對影像結果所帶來的影響，以及各種特性改善的可能性評估。我們利用了真實檢測影像來評估對於EMVA1288的各個參數在檢測器當中的影響，以及各種去雜訊方法對影像品質的影響。 | zh_TW |
| dc.description.abstract | A method of image quality enhancement based on European Machine Vision Association (EMVA1288) as the evaluation method is proposed in this thesis. First we analyze all the EMVA1288 parameters that influence image quality, how the setting of the environment will effect, then we analyze possibility of how these parameters can be improved. We use the real evaluation image to see if all the parameters meet hypothesis. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T07:40:15Z (GMT). No. of bitstreams: 1 ntu-108-R03944034-1.pdf: 6315489 bytes, checksum: 63f9dd0155cefbaf6f80d6f636117832 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi Chapter 1 Introduction 1 1.1 Sensor Defect Estimation 2 1.2 The EMVA1288 Standard 4 Chapter 2 Related Works 6 2.1 EMVA1288 Parameters [2,3] 6 2.1.1 List of parameters to characterize a sensor 7 2.1.2 Linear signal model 7 2.1.3 Noise Model 9 2.1.4 Signal-to-Noise Ratio (SNR) 12 2.1.5 Signal Saturation and Absolute Sensitivity Threshold 13 2.1.6 Dark Current 15 2.1.7 Spatial Nonuniformity 16 Chapter 3 Noise Reduction Method 19 3.1 Noise Reduction Basic 19 3.2 Median Filter 20 3.3 Gaussian Bilateral Filter [4] 21 3.4 Non-Local Means (NL-Means) [1] 22 Chapter 4 Methodology 24 4.1 Noise Reduction Limitation 24 4.2 Our Proposed Method 24 Chapter 5 Experimental Results 28 5.1 Experiment Environment and Dataset 28 5.2 Evaluation of the EMVA1288 Standard 29 5.3 Evaluation of the Noise Type 29 5.4 Experiment on Real Image 30 Chapter 6 Conclusion and Future Work 71 6.1 Conclusion 71 6.2 Future Work 71 REFERENCE 72 | |
| dc.language.iso | en | |
| dc.subject | 雜訊 | zh_TW |
| dc.subject | 雜訊消除 | zh_TW |
| dc.subject | noise | en |
| dc.subject | noise level estimation | en |
| dc.subject | EMVA1288 | en |
| dc.title | 使用EMVA1288評估與降低雜訊 | zh_TW |
| dc.title | Noise Estimation and Reduction with EMVA1288 | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔡安智,施明煌,沈立健 | |
| dc.subject.keyword | 雜訊,雜訊消除, | zh_TW |
| dc.subject.keyword | noise,noise level estimation,EMVA1288, | en |
| dc.relation.page | 72 | |
| dc.identifier.doi | 10.6342/NTU201900373 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-02-15 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位： | 資訊網路與多媒體研究所 | |
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