臺灣博碩士論文加值系統

傳統電視訊號是採用隔行掃描方式(Interlaced Scan)播放，並以交錯式掃描儲存。但在早期傳輸頻寬速率低及一般陰極射線管(CRT)顯示器硬體掃描速率較慢情況下，播放出來的視訊會有像是畫面抖動、閃爍、條紋甚至邊緣部分產生模糊化現象。為了解決這些情況，目前也已有很多解交錯的方法來針對這些現象做強化以達到更好的效果。本論文對於影像部分提出一個低複雜度之空間域影像解交錯演算法，計算五個不同方向像素差異值，並針對影像邊緣較傾斜的部分以及影像內容較為複雜的背景做優化。實驗結果可得知我們提出的方法在影像邊緣及內容較複雜的效果較優於其他解交錯之方法。

Traditional television signal broadcasted and stored by interlaced scanning. In early low transmit speed and low scan rate by traditional Cathode ray tube (CRT) monitor, videos after broadcasted will lead to those conditions like flutter, line flickered even blurring happened at edge regions. In order to solve those conditions, Many De-interlacing methods were proposed to deal with conditions above description to achieve better performance.
In this thesis, we proposed a low-complexity intra-frame de-interlacing method for image. We calculated five pixel differences in five directions, and focus on slope edge and complex contents in image.
As the result, we can obviously find that our method have better performance than other known methods for image in edge regions and complex contents.

摘 要 i
ABSTRACT ii
致 謝 iii
目 錄 iv
表目錄 v
圖目錄 vi
第一章、緒論 1
1.1研究背景及動機 1
1.2論文架構 2
第二章、各類影像解交錯原理概述 3
2.1空間域解交錯處理 4
2.1.1 LD(Line Doubling) 4
2.1.2 LA(Line Average) 5
2.1.3 ELA(Edge Based Line Average) 7
2.1.4 M-ELA(Modified Edge Based Line Average) 8
2.1.5 HIRA(Hybrid Image Restoring Algorithm) 10
2.2時間域解交錯處理 12
2.2.1 Weave 12
2.2.2 STELA(Spatial-Temporal Edge-Based Median Filtering) 13
第三章、提出的低複雜度空間域解交錯法 15
第四章、實驗結果 21
4.1影像品質評比 21
4.1.1平均平方誤差(Mean Square Error, MSE) 21
4.1.2尖峰訊號雜訊比(Peak Signal to Noise Ratio, PSNR) 21
4.2實驗結果分析與比較 22
第五章、結論與未來方向 29
參考文獻 30

[1] 楊大宗，“適應性移動補償的空間-時間域之解交錯演算法”，中原大學光機電及資電控研發碩士專班碩士論文，2007.

[2] 吳博聞， “基於區域特徵之空間-時間域的影像內插方法之研究” ，國立高雄應用科技大學電子工程系碩士論文，2012.

[3] R. S. Prodan, “Multidimensional Digital Signal Processing for Television Scan Conversion,” Phillips J. Res. 41, pp. 576-603, 1986.

[4] T. Doyle, “Interlaced to Sequential Conversion for EDTV Applications,” Proc. 2nd Int. Workshop on Signal Processing of HDTV, pp. 412-430, Feb. 1988.

[5] E. B. Bellers and G. de Haan, “Advanced de-interlacing techniques,” in Proc. ProRISC/IEEE Workshop on Circuits, Systems and Signal Processing, Mierlo, The Netherlands, pp. 7-17, Nov. 1996.

[6] Hyo-Sub Oh, Yoon Kim, You-Young Jung, Aldo W. Morales and Sung Jea Ko, “Spatio-temporal edge-based median filtering for deinterlacing,” IEEE International Conference on Consumer Electronics, pp. 52-53, 2000.

[7] W. Kim, S. Jin and J. Jeong, “Novel intra deinterlacing algorithm using content adaptive interpolation,” IEEE Trans. Cons. Electron. Vol.53, No.3, pp. 1036-1043, Aug. 2007.

[8] C.-Y. Lien, C.-P. Young, and P.-Y. Chen, “A Hybrid Image Restoring Algorithm for Interlaced Video,” IEEE Signal Processing Letter, vol. 16, no. 3, pp. 223-226, Mar. 2009.

[9] P.-Y. Chen and Y.-H. Lai, “A low-complexity interpolation method for deinterlacing,” IEICE Trans. Inf. Syst., vol. E90-D, no. 2, pp.606 -608, 2007.

[10] Ying-Ru Chen and Shen-Chuan Tai, “True Motion-Compensated De-Interlacing Algorithm,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 19, No.10, pp. 1489-1498, Oct. 2009.

[11] J. Dong and K. N. Ngan, “Real-time de-interlacing for H.264-coded HD videos,” IEEE Trans. Circ. Syst. Video Technol., vol. 20, no. 8, pp. 1144-1149, Aug. 2010.

[12] G. Jeon, M. Anisetti, J. Lee, V. Bellandi and J. Jeong, “Concept of linguistic variable-based fuzzy ensemble approach: application to interlaced HDTV sequences,” IEEE Transactions on Fuzzy Systems, vol. 17, no. 6, pp. 1245–1258, Dec. 2009.

[13] Sang-Jun Park, Changki Min, Jechang Jeong and Gwanggil Jeon, “Adaptive Weighting Scheme for Edge-based Line Interpolation,” Image and Video Technology (PSIVT), 2010 Fourth Pacific-Rim Symposium on, pp. 320-324, Nov. 2010.

[14] J. Gutiérrez-Ríos, P. Brox, F. Fernández-Hernández, I. Baturone and S. Sánchez-Solano, “Fuzzy motion adaptive algorithm and its hardware implementation for video de-interlacing,” Applied Soft Computing, vol. 11, no. 4, pp. 3311–3320, Jun. 2011.

[15] X. Chen, G. Jeon and J. Jeong, “Filter switching interpolation method for deinterlacing,” in Optical Engineering, 51, (10), 2012.

[16]J. Wang, G. Jeon and J. Jeong, “Iterative second-order derivative-based deinterlacing algorithm,” Signal Processing: Image Communication, vol. 28, no. 5, pp. 472-482, May. 2013.

[17] M. Trocan, B. Mikovicova, D. Zhanguzin, “An adaptive motion-compensated approach for video deinterlacing,” Multimedia Tools and Applications, Appl. 61(3), pp. 819–837, 2012.

[18] S. Dikbas and Y. Altunbasak, “Novel true-motion estimationalgorithm and its application to motion-compensated temporal frame interpolation,” IEEE Trans. Image Process., vol. 22, no. 8, pp.2931-2945, 2013.

[19] K. Lee and C. Lee, “High quality spatially registered vertical temporal filtering fordeinterlacing,” IEEE Trans. Consum Electron., vol. 59, no. 1, pp.182-190, 2013.

[20] V. Jakhetiya, O. C. Au, S. Jaiswal, L. Jia and H. Zhang, “Fast and efficient intra-frame deinterlacing using observation model based bilateral filter,” IEEE International Conference on Acoustic, Speech and Signal Processing, pp. 5819- 5823, 2014.

[21] J. Wang, G. Jeon and J. Jeong, “Deinterlacing algorithm using weighted least squares,” in IEEE Trans. on circuit and systems for video technology, accepted, in press. 2014.