請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44599完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅楸善(Chiou-Shann Fuh) | |
| dc.contributor.author | Yi-Hung Chou | en |
| dc.contributor.author | 周奕宏 | zh_TW |
| dc.date.accessioned | 2021-06-15T03:51:35Z | - |
| dc.date.available | 2015-07-15 | |
| dc.date.copyright | 2010-07-15 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-07-13 | |
| dc.identifier.citation | [1] C. Y. Chong, “Image Noise Reduction with Frequency Analysis,” Master Thesis, Department of Computer Science and Information Engineering, National Taiwan University, 2008.
[2] Nokia & ST, “SMIA 1.0,” http://www.kminstrument.co.kr/admin%5Cdata%5Cupload%5CSMIA_Characterisation_Specification.pdf, 2010. [3] R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, Vol. I, Addison Wesley, Reading, MA, 1992. [4] Skype, “Skype Hardware Certification Specification,” http://www.megaupload.com/?d=DCRMO1Q6, 2010. [5] Y. H. Chou, “Video Flash,” http://www.csie.ntu.edu.tw/~fuh/gif/video%20flash.avi, 2010. [6] Youtube, “Beast,” http://www.youtube.com/watch?v=QSkeB_WfemE, 2010. [7] Y. Zhao and L. Yu, “A Video Quality Assessment Method,” http://www.megaupload.com/?d=M48G2ZYV, 2010. [8] Wikipedia, “Signal-to-Noise Ratio,” http://en.wikipedia.org/wiki/Signal-to-noise_ratio, 2010. [9] Wikipedia, “Wikipedia,” http://en.wikipedia.org/wiki/Wikipedia, 2010. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44599 | - |
| dc.description.abstract | 在一般視訊的雜訊量測，是採用擷取一張影像來代表這段影像。可是這並不是個十分合理的現象，因為每一秒就包含了30張的影像。而量測一連串的影像雜訊，更是必需要考慮同一像素的時間關聯性。基於一般影像的雜訊量測使用噪訊比，我們提出的方法是一個有考慮到時間的噪訊比量測方法。
在很多雜訊處理的演算法都有很多取捨，我們更需要一個好的測量的基準。因此這篇論文提出了一些雜訊的量測方法並提供了一種新的測量方式。 | zh_TW |
| dc.description.abstract | When we need to analyze video images, we sometimes capture one still image. But the video is 30 FPS (Frame per Second). But using only one static image to represent this video is unreasonable. Moreover, we must consider the impact of temporal noise. Our method is based on SNR (Signal-to-Noise Ratio) with time relevance of each pixel.
Many noise reduction algorithms have many trade-offs. We need a good measurement method. Therefore this thesis proposes some noise measurement methods and provides one new measurement mode. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T03:51:35Z (GMT). No. of bitstreams: 1 ntu-99-R97944037-1.pdf: 2748029 bytes, checksum: af3b824146b807170b2d96b9a2dba2e3 (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌 謝 ii 摘 要 iii Abstract iv Content v Figure Content viii Table Content ix Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Noise in Static Image 2 1.2.1 Fixed Pattern Noise 2 1.2.2 Banding Noise 2 1.2.3 Random Noise 3 1.3 Static Image Noise Characteristics 3 1.4 Noise in Video 5 Chapter 2 Previous Noise Measurements 8 2.1 Description 8 2.2 Related Works 8 2.3 Normal SNR (Signal-to-Noise Ratio) 10 2.3.1 Description 10 2.3.2 Formula 10 2.3.3 Pseudo-code 11 2.4 Column Noise 12 2.4.1 Description 12 2.4.2 Formula 12 2.4.3 Pseudo-code 12 2.5 Row Noise 13 2.5.1 Description 13 2.5.2 Formula 13 2.5.3 Pseudo-code 13 2.6 Frame-to-Frame Flicker (FFF) 14 2.6.1 Description 14 2.6.2 Formula 14 2.6.3 Pseudo-code 14 2.7 Temporal Noise 15 2.7.1 Description 15 2.7.2 Formula 15 2.7.3 Pseudo-code 15 2.8 Signal-to-Noise Ratio 16 2.8.1 Description 16 2.8.2 Formula 16 2.8.3 Pseudo-code 16 Chapter 3 Our Method VSNR 17 3.1 Description 17 3.2 Our Method 17 3.2.1 Scene 17 3.2.2 Record 18 3.2.3 Calculate 18 3.3 Formula of VSNR 19 3.4 VSNR Flow Chart 20 3.5 Pseudo code 21 3.6 Down Sample 21 Chapter 4 Experimental Result 23 4.1 Justify 24 4.1.1 Forecast 24 4.1.2 Experimental Result 25 4.2 Vote and Compare with SMIA Spatial SNR. 28 4.2.1 Forecast 28 4.2.2 Experimental Result 29 4.3 Flash Noise Measurement 34 4.3.1 Forecast 34 4.3.2 Experimental Result 34 4.4 Processing Time 39 4.5 Conclusion 40 Chapter 5 Future Work 41 Reference 42 | |
| dc.language.iso | en | |
| dc.subject | 時間噪訊比 | zh_TW |
| dc.subject | 雜訊 | zh_TW |
| dc.subject | 視訊雜訊 | zh_TW |
| dc.subject | 視訊雜訊量測 | zh_TW |
| dc.subject | 影像 | zh_TW |
| dc.subject | 噪訊比 | zh_TW |
| dc.subject | video noise | en |
| dc.subject | Temporal SNR | en |
| dc.subject | SNR | en |
| dc.subject | video noise measurement | en |
| dc.subject | noise | en |
| dc.title | 視訊影像雜訊分析與量測方法 | zh_TW |
| dc.title | Video Image Noise Analysis and Measurement Methods | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蘇君誠,蔡育良,李恆寬 | |
| dc.subject.keyword | 雜訊,視訊雜訊,視訊雜訊量測,影像,噪訊比,時間噪訊比, | zh_TW |
| dc.subject.keyword | noise,video noise,video noise measurement,SNR,Temporal SNR, | en |
| dc.relation.page | 42 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2010-07-13 | |
| 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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