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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅楸善(Chiou-Shann Fuh) | |
| dc.contributor.author | Pu-Hua Mei | en |
| dc.contributor.author | 梅普華 | zh_TW |
| dc.date.accessioned | 2021-06-13T06:35:53Z | - |
| dc.date.available | 2007-01-26 | |
| dc.date.copyright | 2006-01-26 | |
| dc.date.issued | 2005 | |
| dc.date.submitted | 2006-01-06 | |
| dc.identifier.citation | [1] J. Adams, K. Parulski, and K. Spaulding, “Color Processing in Digital Cameras,” IEEE Micro, Vol. 18, Issue 6, pp. 20-30, 1998.
[2] N. Ahuja and B. J. Schachter, “Image Models,” Computing Surveys, Vol. 13, No. 4, pp.373-397, 1981. [3] M. Almond, “Noise Reduction Tool Comparison,” http://www.michaelalmond.com/Articles/noise_print.html, 2005. [4] D. H. Brainard and W. T. Freeman, “Bayesian Color Constancy,” Journal of the Optical Society of America, A, Vol. 14, pp. 1393-1411, 1997. [5] D. R. K. Brownrigg, “The Weighted Median Filter,” Communications of the ACM, Vol. 27, No. 8, pp. 807-818, 1984. [6] R. L. Carter, “DigiCamHistory.Com,” http://www.digicamhistory.com/1970s.html, 2005. [7] C. C. Chang, J. Y. Hsiao, and C. P. Hsieh, “A Fast Noise Reduction Method Based on Human Visual System,” Proceedings of Joint Conference of the Fourth International Conference on Information Communications and Signal Processing and Fourth Pacific-Rim Conference on Multimedia, Singapore, Vol. 3, pp.1879-1883, 2003. [8] D. Chralampidis, T. Kasparis, and M. Georgiopoulos, “Classification of Noisy Signals Using Fuzzy ARTMAP Neural Networks,” IEEE Transactions on Neural Networks, Vol. 12, Issue 5, pp. 1023-1036, 2001. [9] CIPA, “HYRes 3.1 – The Resolution Measurement Program,” http://www.cipa.jp/dcs/hyres/hyres_1_e.html, 2005. [10] Eastman Kodak Company, “CCD Image Sensor Noise Sources,” http://www.kodak.com/global/plugins/acrobat/en/digital/ccd/applicationNotes/noiseSources.pdf, 2005. [11] Eastman Kodak Company, “Color Correction for Image Sensors,” http://wwwau.kodak.com/global/plugins/acrobat/en/digital/ccd/applicationNotes/ColorCorrectionforImageSensors.pdf, 2003. [12] H. L. Eng and K. K. Ma, “Noise Adaptive Soft-Switching Median Filter,” IEEE Transactions on Image Processing, Vol. 10, No. 2, pp. 242-251, 2001. [13] M. A. Fischler and R. C. Bolles, “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography,” Communications of the ACM, Vol. 24, Issue 6, pp. 381-395, 1981. [14] R. Gonzalez and R. Woods, Digital Image Processing, 2nd Edition, Prentice Hall, Upper Saddle River, NJ, 2002. [15] B. K. Gunturk, Y. Altunbasak, and R. M. Mersereau, “Color Plane Interpolation Using Alternating Projections,” IEEE Transactions on Image Processing, Vol. 11, No.9, pp. 997-1013, 2002. [16] R. M. Haralick and L. G.. Shapiro, Computer and Robot Vision, Vol. I, Addison Wesley, Reading, MA, 1992. [17] ISO, “ISO 12233, Photography – Electronic Still Picture Camera – Resolution Measurements,” ISO/TC 42, 1999. [18] M. H. Kiu and D. C. Banks, “Multi-Frequency Noise for LIC,” Proceedings of Conference on Visualization, San Francisco, CA, pp.121-126, 1996. [19] S. J. Ko and Y. H. Lee, “Center Weighted Median Filters and Their Applications to Image Enhancement,” IEEE Transactions on Circuits and Systems, Vol. 38, No. 9, pp. 984-993, 1991. [20] M. Lahat, R. Niederjohn, and D. Krubsack, “A Spectral Autocorrelation Method for Measurement of the Fundamental Frequency of Noise-Corrupted Speech,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 35, Issue 6, pp.741-750, 1987. [21] H. M. Lin and A. N. Willson, Jr., “Median Filters with Adaptive Length,” IEEE Transactions on Circuits and Systems, Vol. 35, No. 6, pp. 675-690, 1988. [22] G. Luo, “Image Noise Analysis with a Fast Lifting Wavelet Algorithm for Objective Image Quality Evaluation,” Proceedings of International Conference on Image and Graphics, Hong Kong, China, pp. 39-42, 2004. [23] nik Multimedia Inc, “Effective Noise Reduction & Detail Optimization: An Analysis & Post Capture Processing Model,” http://www.nikmultimedia.com/downloads/pdf/usa_pressreleases/NoiseReduction_WhitePaper.pdf, 2003. [24] S. C. Pei and I. K. Tam, “Effective Color Interpolation in CCD Color Filter Arrays Using Signal Correlation,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, No. 6, pp. 503- 513, 2003. [25] R. A. Peters, “A New Algorithm for Image Noise Reduction Using Mathematical Morphology,” IEEE Transactions on Image Processing, Vol. 4, No. 5, pp. 554-568, 1995. [26] C. A. Poynton, “Frequently-Asked Questions about Gamma,” http://www.poynton.com/GammaFAQ.html, 1998. [27] W. K. Pratt, Digital Image Processing, Wiley, New York, 1978. [28] R. Ramanath, W. E. Snyder, and G. L. Bilbro, “Demosaicking Methods for Bayer Color Array,” Journal of Electronic Imaging, Vol. 11, No. 3, pp. 306-315, 2002. [29] R. Ramanth, W. E. Snyder, Y. Yoo, and M. S. Drew, “Color Image Processing Pipeline,” IEEE Signal Processing Magazine, Vol. 22, No. 1, pp. 34-43, 2005. [30] B. W. Silverman, Density Estimation for Statistics and Data Analysis. CRC Press, Boca Raton, FL, 1986. [31] S. M. Smith, “Flexible Filter Neighbourhood Designation,” Proceedings of International Conference on Pattern Recognition, Vienna, Austria, Vol. 1, pp. 206-211, 1996. [32] S. M. Smith and J. M. Brady, “SUSAN - A New Approach to Low Level Image Processing,” International Journal of Computer Vision, Vol. 23, No. 1, pp. 45-78, 1997. [33] S. R. Sternberg, “Grayscale Morphology,” Computer Vision, Graphics, and Image Processing, Vol. 35, Issue 3, pp. 333-355, 1986. [34] 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. [35] N. Trung, “Encyclopedia of Computer Science,” http://www.eleves.ens.fr/home/trung/image_processing.html, 2005. [36] G. K. Wallace, “The JPEG Still Picture Compression Standard,” Communications of the ACM, Vol. 34, Issue 4, pp. 30-44, 1991. [37] X. Wang, “On the Gradient Inverse Weighted Filter,” IEEE Transactions on Signal Processing, Vol. 40, No. 2, pp. 482-484, 1992. [38] X. Wang, “Optimal Edge-Preserving Hybrid Filters,” IEEE Transactions on Image Processing, Vol. 3, Issue 6, pp. 862-865, 1994. [39] M. Westenberg and T. Ertl, “Vector Wavelet Thresholding for Vector Field Denoising,” Proceedings of IEEE Visualization, Austin, TX, p. 598.25, 2004. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34866 | - |
| dc.description.abstract | 雜訊抑制是非常重要的影像處理操戶。所有影像擷取裝置在擷取像素時也會同時取得雜訊，因此雜訊抑制對高品質影像資料的取得影響甚大。雜訊抑制可以在數位相機影像處理流程中由硬體完成，也可以在後處理時以雜訊抑制工具完成。通常硬體作法比較快但後處理佳果比較好。很多雜訊抑制工具提供雜訊側寫功能，可以測量影像擷取裝置的雜訊特性，然後利用此特性更有效地抑制雜訊。大部份工具都是針對一般使用者去處理最後已完成的影像。本文提議將雜訊側寫作為數位相機生產時的校正步驟，並對未處理的原始影像資料進行雜訊抑制，可以在擷取影像時加快處理速度並達到更佳的雜訊抑制效果。 | zh_TW |
| dc.description.abstract | Noise reduction is a very important operation for image processing. All image capture devices capture image pixels and the noise at the same time and noise reduction is needed to retrieve high-quality image data. Noise reduction can be done in digital camera image pipeline by hardware, or it can be done in post processing by noise reduction tools. Generally the hardware approach is faster but post processing achieves better quality. Many noise reduction tools provide noise-profiling feature which measures the noise characteristic of image capture devices and uses the profiling result to reduce the noise more efficiently. Most of the tools are designed for end users to reduce noise of final image. This paper proposes using noise profiling as a calibration step in digital camera manufacturing and reducing noise in raw data color space. The benefit is faster and better noise reduction during image capture. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T06:35:53Z (GMT). No. of bitstreams: 1 ntu-94-P92922005-1.pdf: 945923 bytes, checksum: 3b2b0aaba919cecdf13986a74174ce7a (MD5) Previous issue date: 2005 | en |
| dc.description.tableofcontents | Chapter 1 Introduction 1
1.1 Noise Reduction 1 1.2 Calibration 1 1.3 Digital Camera Image Pipeline 2 1.3.1 Data Format in Digital Camera Image Pipeline 2 1.3.2 Optical Black Clamping 3 1.3.3 White-Balance 4 1.3.4 Color Interpolation 6 1.3.5 Color Correction 7 1.3.6 Gamma Correction 10 1.3.7 Edge Enhancement 11 1.3.8 Compression 11 Chapter 2 Previous Works 12 2.1 Noise Estimation 12 2.1.1 Noise Amplitude 12 2.1.2 Spatial Frequency of Noise 17 2.2 Image Noise Reduction 17 Chapter 3 Digital Camera Image Noise Analysis 19 3.1 Noise Source of Image Sensor and Circuit 19 3.1.1 Shot Noise 19 3.1.2 Dark Current Noise 19 3.1.3 Read Noise 19 3.1.4 Others Noise Sources 19 3.1.5 Overall Noise Analysis of Image Sensor and Circuit 19 3.2 Noise Source of Digital Camera Image Pipeline 23 3.2.1 Optical Black Clamping 23 3.2.2 White-Balance 23 3.2.3 Color Interpolation 23 3.2.4 Color correction 24 3.2.5 Gamma Correction 24 3.2.6 Edge Enhancement 27 3.2.7 Compression 27 3.2.8 Overall Noise Analysis of Image Pipeline 28 Chapter 4 Image Noise as Unit-Dependent Characteristic 30 4.1 Image Sensor and Circuit Noise as Unit-Dependent Characteristic 30 4.2 Image Pipeline Noise as Unit-Dependent Characteristic 31 Chapter 5 Noise Reduction in Raw Data Color Space 33 5.1 Noise Amplitude Histogram 33 5.1.1 Raw Noise Amplitude Histogram 33 5.1.2 Noise Amplification Curve of Image Pipeline 33 5.1.3 Noise Amplitude Histogram after Image Pipeline 33 5.2 Noise Reduction in Raw Data Color Space 35 5.2.1 Noise Reduction for Raw Data with Bayer Pattern 35 5.2.2 Applying Noise Amplitude Histogram 36 5.2.3 Noise Reduction Filter 36 Chapter 6 Comparison 38 6.1 Test Method 38 6.2 Visual Inspection Analysis 39 6.3 Standard Deviation Analysis 40 6.4 Processing Time 41 6.5 Impact on Resolution 42 Chapter 7 Conclusion and Future Work 44 7.1 Conclusion 44 7.2 Future Work 44 Chapter 8 Biblography 46 | |
| dc.language.iso | en | |
| dc.subject | 校正 | zh_TW |
| dc.subject | 數位影像 | zh_TW |
| dc.subject | 雜訊 | zh_TW |
| dc.subject | noise reduction | en |
| dc.subject | calibration | en |
| dc.subject | image | en |
| dc.title | 以校正去除數位相機的雜訊 | zh_TW |
| dc.title | Digital Camera Image Noise Reduction with Calibration | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 94-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 劉顯仲,葉錫麟 | |
| dc.subject.keyword | 校正,雜訊,數位影像, | zh_TW |
| dc.subject.keyword | image,noise reduction,calibration, | en |
| dc.relation.page | 48 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2006-01-09 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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