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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 王傑智 | |
dc.contributor.author | "Yang, Yao-Hsiang" | en |
dc.contributor.author | 楊耀翔 | zh_TW |
dc.date.accessioned | 2021-05-17T09:14:34Z | - |
dc.date.available | 2014-08-17 | |
dc.date.available | 2021-05-17T09:14:34Z | - |
dc.date.copyright | 2012-08-17 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-08-15 | |
dc.identifier.citation | References
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/6545 | - |
dc.description.abstract | 自然影像統計,對於計算視覺社群的研究者而言,在過去二十年間早已引發相當的興趣。已有不少研究報告在許多的不同條件下收集到的影像資料之不同特徵。相較於其他不對影像作明確假設的應用,基於自然影像統計假設的許多應用研究也已證明相當有用並易於理解。
在本文中,我希望摘要那些過去研究的實驗結果與解釋。而後,我希望調查這些事實在研究中可以扮演的角色。在闡釋理論的架構之後,兩項新的應用,分別利用費雪判別分析與維納濾波,將被推演用以展示這一方法的效力。我希望這些初步的結果能顯示足夠的前途,讓人們對未來發展更加完備的影像分析之形式理論有足夠信心。 | zh_TW |
dc.description.abstract | Natural image statistics has long been interested by the researchers of the computer vision community during the last twenty years. There has been reports on many distinct characteristics of image data collecting under various conditions. Several applications based on the assumptions derived from natural image statistics have been proved to be both useful and intelligible in compare to those works which do not employ any explicit assumptions about images.
In this thesis, I wish to summarize those experimental results and explanations in previous studies. Then I wish to investigate the role of these facts in the research. After explicating the theoretical framework, two novel applications incorporating the Fisher's discriminant analysis and Wiener filtering are conduct in order to demostrate the power of this approach. I wish these rudimentary results are shown to be promising enough to make people more confident about the possible future toward a more complete formal theory of image analysis. | en |
dc.description.provenance | Made available in DSpace on 2021-05-17T09:14:34Z (GMT). No. of bitstreams: 1 ntu-101-R99944017-1.pdf: 1325559 bytes, checksum: 16993ee0f2a613f04f2fc3b0c35cf4c0 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | Contents
中文摘要ii 致謝iii List of Figures vi List of Tables vii 1 Introduction 1 2 Basic Interpretation of Natural Image Statistics 2 3 Application: Fisher’s Discriminant Analysis 4 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.1 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.2 The Models of the Natural Images . . . . . . . . . . . . . . . . . . . 8 3.3 Fisher’s Discriminant with Natural Image Priors . . . . . . . . . . . . 10 3.3.1 Penalized Discriminant Analysis: a special S-Assumption . . . 13 3.3.2 M-Assumption . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.3.3 Proposed method: approximated M-Assumption + S-Assumption 15 3.4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.4.1 Face Recognition . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.4.2 Object Categorization . . . . . . . . . . . . . . . . . . . . . . 19 3.5 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 iv 4 Application: Illumination Invariant Feature Extraction 21 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.1.1 Illumination-Invariant Feature Extraction . . . . . . . . . . . 21 4.2 Wiener Filtering for Natural Illumination . . . . . . . . . . . . . . . . 26 4.3 Verification of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 4.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4.5 Conclusion and Future Works . . . . . . . . . . . . . . . . . . . . . . 39 5 References 42 | |
dc.language.iso | en | |
dc.title | 自然影像的機率分析 | zh_TW |
dc.title | A Probabilistic Analysis of Natural Images | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 陳祝嵩 | |
dc.contributor.oralexamcommittee | 李明穗,石勝文 | |
dc.subject.keyword | 自然影像統計,降維,光照不變特徵抽取,貝氏分析,維納濾波, | zh_TW |
dc.subject.keyword | natural image statistics,dimension reduction,illumination-invariant feature extraction,Bayesian analysis,Wiener filtering, | en |
dc.relation.page | 48 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2012-08-15 | |
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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