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Author: 陳思妮
Szu-Ni Chen
Thesis Title: 基於自適應雙線性插值法之針對彩圖的迭代彩度抽樣方法
An Adaptive Bilinear Interpolation­-based Iterative Chroma Subsampling Method for Color Images
Advisor: 鍾國亮
Kuo-Liang Chung
Committee: 蔡文祥
顏嗣鈞
李同益
鍾國亮
花凱龍
Degree: 碩士
Master
Department: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
Thesis Publication Year: 2021
Graduation Academic Year: 109
Language: 英文
Pages: 50
Keywords (in Chinese): 拜耳彩色濾光片陣列圖像彩度抽樣凸塊失真函數數字延時積分彩色濾光片陣列圖像質量比特率權衡品質提升全彩圖像
Keywords (in other languages): Bayer color filter array (CFA) image, chroma subsampling, convex block-distortion function, digital time delay integration CFA image, quality-bitrate tradeoff, quality enhancement, RGB full-color image
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在對彩色圖像,例如RGB全彩色圖像 I^{RGB},拜耳彩色濾光片陣列圖像 I^{Bayer} 或數字延時積分CFA圖像 I^{DTDI},進行編碼之前,對轉換後的彩度圖像執行彩度抽樣是必要的步驟。
以前,分別為 I^{RGB}、I^{Bayer} 和 I^{DTDI} 開發了數種彩度抽樣方法。
在本文中,我們同時考慮三種圖像類型,提出了一種基於自適應雙線性插值的迭代彩度抽樣方法,以重建更佳的重構圖像。
綜合從 Kodak、IMAX 和 SCI 數據集收集的三種圖像類型,實驗結果表明,在多功能視頻編碼(VVC)平台下,我們的自適應彩度抽樣方法之重構圖像與現存的彩度抽樣方法相比具有最佳質量和BD-PSNR。


Prior to encoding a color image, such as the RGB full-color image $I^{RGB}$, the Bayer color filter array (CFA) image $I^{Bayer}$, or the digital time delay integration CFA image $I^{DTDI}$, performing chroma subsampling on the converted chroma image is a necessary step.
Previously, several chroma subsampling methods were developed for $I^{RGB}$, $I^{Bayer}$, and $I^{DTDI}$ independently.
In this thesis, we propose an effective bilinear interpolation-based iterative chroma subsampling method for the considered three image types simultaneously, achieving better reconstructed images.
Based on the considered three types of images collected from the Kodak, IMAX, and SCI (screen content images), the comprehensive experimental results demonstrated that under the versatile video coding (VVC) platform, our chroma subsampling method achieves the best quality and quality-bitrate tradeoff of the reconstructed color images when compared with the existing chroma subsampling methods.

指導教授推薦書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i 論文口試委員審定書. . . . . . . . . . . . . . . . . . . . . . . . . . . . ii Abstract in Chinese . . . . . . . . . . . . . . . . . . . . . . . . . . iii Abstract in English . . . . . . . . . . . . . . . . . . . . . . . . . . iv Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix List of Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . x 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Related works . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1.1 Related works for I^{Bayer} . . . . . . . . . . . . . . . . . . . . 4 1.1.2 Related works for I^{DTDI} . . . . . . . . . . . . . . . . . . . . . 6 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 The proposed BILI-based block-distortion function . . . . . . . . . . . . 10 3 The proposed BILI-based iterative chroma subsampling method . . . . . . . 14 3.1 Convex property proof of the proposed block-distortion function . . . . 14 3.2 Determining the initial subsampled chroma solution . . . . . . . . . . . 16 3.3 The proposed BILI-based iterative chroma subsampling method . . . . . . . 19 4 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.1 Quality enhancement merit of our method and time comparison . . . . . . 22 4.1.1 For I^{RGB} . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.1.2 For I^{Bayer} . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.1.3 For I^{DTDI} . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 4.2 Quality-bitrate tradeoff and visual effect merits of our method . . . . . 27 4.2.1 The quality-bitrate tradeoff merit in terms of RD curves . . . . . . . 28 4.2.2 The BD-PSNR merit . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

[1] B. E. Bayer, “Color imaging array,” Jul 1976. US Patent 3,971,065.
[2] R. Lukac and K. N. Plataniotis, “Color filter arrays: design and performance analysis,” IEEE Transactions on Consumer Electronics, vol. 51, no. 4, pp. 1260–1267, 2005.
[3] E. Bodenstorfer, J. Fürtler, J. Brodersen, K. J. Mayer, C. Eckel, K. Gravogl, and H. Nachtnebel, “Highspeed line-scan camera with digital time delay integration,” in Real-Time Image Processing 2007, vol. 6496, p. 64960I, International Society for Optics and Photonics, Feb 2007.
[4] L. Zhang, X. Wu, A. Buades, and X. Li, “Color demosaicking by local directional interpolation and nonlocal adaptive thresholding,” Journal of Electronic Imaging, vol. 20, pp. 023016–1–023016–16, Jun. 2011.
[5] D. Kiku, Y. Monno, M. Tanaka, and M. Okutomi, “Residual interpolation for color image demosaicking,” in 2013 IEEE International Conference on Image Processing, pp. 2304–2308, Sep 2013.
[6] X. Li, B. Gunturk, and L. Zhang, “Image demosaicing: A systematic survey,” in Visual Communications and Image Processing 2008, vol. 6822, p. 68221J, International Society for Optics and Photonics, Jan 2008.
[7] D. S. Tan, W. Y. Chen, and K. L. Hua, “DeepDemosaicking: Adaptive image demosaicking via multiple deep fully convolutional networks,” IEEE Transactions on Image Processing, vol. 27, pp. 2408– 2419, May 2018.
[8] Z. Ni, K. K. Ma, H. Zeng, and B. Zhong, “Color image demosaicing using progressive collaborative representation,” IEEE Transactions on Image Processing, vol. 29, pp. 4952–4964, 2020.
[9] ITU-R, “BT6015: Studio encoding parameters of digital television for standard 4:3 and widescreen 16:9 aspect ratios,” International Telecommunications Union, 2011.
[10] J. Ridge and M. Karczewicz, “Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG (ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q. 6),” 2007.
[11] Y. Zhang, D. Zhao, J. Zhang, R. Xiong, and W. Gao, “Interpolation-dependent image downsampling,” IEEE Transactions on Image Processing, vol. 20, pp. 3291–3296, Nov. 2011.
[12] S. Wang, K. Gu, S. Ma, and W. Gao, “Joint chroma downsampling and upsampling for screen content image,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, pp. 1595–1609, Sep. 2016.
[13] X. Li and M. T. Orchard, “New edge-directed interpolation,” IEEE Transactions on Image Processing, vol. 10, pp. 1521–1527, Oct. 2001.
[14] J. Allebach and P. W. Wong, “Edge-directed interpolation,” in Proceedings of 3rd IEEE International Conference on Image Processing, vol. 3, pp. 707–710 vol.3, 1996.
[15] Y. Lu, S. Li, and H. Shen, “Virtualized screen: A third element for cloud–mobile convergence,” IEEE Multimedia Magazine, vol. 18, pp. 4–11, Feb. 2011.
[16] H. Chen, M. Sun, and E. Steinbach, “Compression of Bayer-pattern video sequences using adjusted chroma subsampling,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, pp. 1891–1896, Dec. 2009.
[17] C. H. Lin, K. L. Chung, and C. W. Yu, “Novel chroma subsampling strategy based on mathematical optimization for compressing mosaic videos with arbitrary RGB color filter arrays in H. 264/AVC and HEVC,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, pp. 1722–1733, Sep. 2016.
[18] K. L. Chung, Y. L. Lee, and W. C. Chien, “Effective gradient descent-based chroma subsampling method for Bayer CFA images in HEVC,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, pp. 3281–3290, Nov. 2019.
[19] T. L. Lin, Y. C. Yu, K. H. Jiang, C. F. Liang, and P. S. Liaw, “Novel chroma sampling methods for CFA video compression in AVC, HEVC and VVC,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, pp. 3167–3180, Sep. 2020.
[20] Y. C. Yu, J. W. Jhang, X. Wei, H. W. Tseng, Y. Wen, Z. Liu, T. L. Lin, S. L. Chen, Y. S. Chiou, and H. Y. Lee, “Chroma upsampling for YCbCr 420 videos,” in 2017 IEEE International Conference on Consumer Electronics Taiwan (ICCE-TW), pp. 163–164, Jun 2017.
[21] K. L. Chung, W. J. Yang, C. H. Chen, H. Y. M. Liao, and S. M. Zeng, “Efficient chroma subsampling strategy for compressing digital time delay integration mosaic video sequences in H.264/AVC,” Journal of Electronic Imaging, vol. 20, pp. 1 – 16, Apr. 2011.
[22] G. Bjøntegaard, “Calculation of average psnr differences between rd-curves (vceg-m33),” in document VCEG-M33, pp. 2–4, 13th ITU-T Video Coding Experts Group (VCEG) Meeting, Austin, TX, USA, 2001.
[23] Eastman Kodak Company, “Kodak dataset,” 2014.
[24] L. Zhang, X. Wu, A. Buades, and X. Li, “IMAX dataset,” 2014.
[25] SCI Image Database, 2021.
[26] ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group, “VTM-8.0,” 2020.
[27] B. N. Datta, Numerical linear algebra and applications. Philadelphia, PA, USA: Brooks/Cole, 1st ed ed., 1995.
[28] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Transactions on Image Processing, vol. 13, pp. 600–612, Apr. 2004.
[29] L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM: A feature similarity index for image quality assessment,” IEEE Transactions on Image Processing, vol. 20, pp. 2378–2386, Aug. 2011.
[30] C. Babu, D. A. Chandy, and P. Karthigaikumar, “Novel chroma subsampling patterns for wireless capsule endoscopy compression,” Neural Computing and Applications, vol. 32, pp. 6353–6362, May. 2020.

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