博碩士論文 93541001 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:73 、訪客IP:3.144.17.207
姓名 謝慶發(Chin-Fa Hsieh)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 整合類比數位轉換與二維離散小波轉換於視訊 影像處理的系統晶片設計
(A SoC Integrating ADC and 2DDWT for Video/Image Processing)
相關論文
★ 即時的SIFT特徵點擷取之低記憶體硬體設計★ 即時的人臉偵測與人臉辨識之門禁系統
★ 具即時自動跟隨功能之自走車★ 應用於多導程心電訊號之無損壓縮演算法與實現
★ 離線自定義語音語者喚醒詞系統與嵌入式開發實現★ 晶圓圖缺陷分類與嵌入式系統實現
★ 語音密集連接卷積網路應用於小尺寸關鍵詞偵測★ G2LGAN: 對不平衡資料集進行資料擴增應用於晶圓圖缺陷分類
★ 補償無乘法數位濾波器有限精準度之演算法設計技巧★ 可規劃式維特比解碼器之設計與實現
★ 以擴展基本角度CORDIC為基礎之低成本向量旋轉器矽智產設計★ JPEG2000靜態影像編碼系統之分析與架構設計
★ 適用於通訊系統之低功率渦輪碼解碼器★ 應用於多媒體通訊之平台式設計
★ 適用MPEG 編碼器之數位浮水印系統設計與實現★ 適用於視訊錯誤隱藏之演算法開發及其資料重複使用考量
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 行車紀錄系統與監控系統均會呈現多個畫面,同時顯示在一螢幕上,此需具有影像縮小之功能。為了作系統整合之考量,若能將此縮小影像之功能與類比數位轉換器整合成一晶片,則可簡化系統設計之複雜度,本文以此為目的提出類比數位整合之系統晶片(System on a Chip, SoC)設計。

在二維離散小波轉換(2-Dimensional Discrete Wavelet Transform)的設計中,記憶體對其效能的評估具有重要之角色,傳統的二維離散小波轉換設計中需動態記憶體去儲存輸入影像與記憶體儲存行列轉換間之暫時資料,類比數位轉換器(analog-to-digital converter )為攝影模組之基本模組,本論文提出一整合類比數位轉換器與高記憶體使用效能的二維離散小波轉換系統晶片設計供視訊/影像處理用,後者僅包含列處理器和行處理器兩個主要模組。在行處理器中使用內部環型移位暫存器(Internal Ring Shift Registers,IRSR),所提出的架構可以不使用動態記憶體並降低記憶體使用量,管線技術也用在二維離散小波轉換電路以縮短臨界路徑的延遲到一個加法器的時間。所提出的架構使用較少的記憶體及較簡單之控制電路而優於現有的架構,對一個N×N個圖像,就二維一階5/3上提式離散小波轉換而言,內部環型移位暫存器僅需要2N個暫存器,而不需使用傳統架構的3.5N 個記憶體, 除此之外,時脈門控技術也用於內部環型移位暫存器以減少功率消耗。

所提出的2DDWT架構以Verilog HDL設計並以TSMC 0.18微米的標準元件庫合成與驗證。類比數位轉換器則以全客戶示設計而成為一個矽智財(Intellectual Property),之後以混合模式的設計流程整合為系統晶片,本論文不需要外部記憶體,降低了由記憶體存取與數位類比晶片整合I / O腳的功耗,同時也降低了印刷電路板的大小。所提架構具有10位元解析度,可與CMOS影像感測器(CMOS Image Sensor)或其它矽智財進一步整合供以離散小波轉換為基礎之視訊編碼使用。

摘要(英) Driving record systems and monitoring systems will display multiple pictures simultaneously on a screen, which requires a narrow function to shrink images. For the system integration consideration, if the Analog to Digital Converter and shrink image circuit can be integrated into a chip, the complexity of the system design can be simplified. Based on this motivation, the integration of analog circuit and digital circuit is presented in this work.

The memory issue plays a very important role for the performance evaluation of a design of 2-Dimensional Discrete Wavelet Transform (2DDWT). A traditional 2DDWT architecture generally needs DRAM to store the input pixel and memory to store temporary results between row and column processors. In this paper, we present a system on a chip (SoC) for video/image processing. The chip integrates an analog-to-digital converter (ADC) with a highly efficient-memory 2DDWT. The latter one contains two main components only: a row processor and a column processor. With this integrated chip plus the use of Internal Ring Shift Registers (IRSR) in the column processor, the proposed architecture can disuse the DRAM and reduce the memory. The pipelined technique is also utilized in the proposed 2DDWT to shorten the critical path to an adder delay. The proposed architecture outperforms the existing architectures in that it uses less memory size and has low control complexity. It needs only 2N register instead of a 3.5N register of traditional architectures for a one-level 2DDWT of the 5/3 Lifting-based Discrete Wavelet Transform (LDWT) in an N x N image. Besides, The clock gating technique is also applied to the IRSR for power reduction.

The proposed 2DDWT architecture is coded in VerilogHDL and the Synopsys Design Compiler is employed to synthesize the design with the standard-cell from TSMC 0.18 μm cell library for verification. The ADC is designed by a full-custom methodology, plays as an IP of the SoC. With the integrated SoC, based on the mix-mode design flow, the proposed work requires no external memory, which accordingly reduces the power consumption by memory access and I/O PADs, it also reduces the printed circuit board (PCB) size. Moreover, the proposed SoC supports the resolution of 10 bits and can easily integrate further with the CMOS image sensor (CIS) or other IPs. This, then, completes a single chip and makes ready for the application to a real-time wavelet-based video coding.

關鍵字(中) ★ 系統晶片
★ 離散小波轉換
★ 類比數位轉換器
★ CMOS影像感測器
關鍵字(英) ★ SoC
★ Discrete Wavelet Transform
★ analog-to-digital converter
★ CMOS Image Sensor
論文目次 CHAPTER 1

INTRODUCTION 1

1.1 System Overview 1

1.2 Motivation 4

1.3 Background 6

1.4 Dissertation Organization 7

CHAPTER 2

DESIGN CONSIDERATIONS 8

2.1 Choice of ADC 8

2.2 Choice Image Processor ….....………………………………………………..……10

CHAPTER 3

PRINCIPLE OF PIPELINE ADC 11

3.1 Introduction to A-to-D Converters 11

3.2 Pipelined ADC Architecture …………………………………………………..…..14

CHAPTER4

PRINCIPLE OF DWT 17

4.1 Background 17

4.2 Lifting Scheme DWT …….…………………………………………………..……20

CHAPTER 5

PROPOSED ARCHITECTURE 23

5.1 Overview 23

5.2 ADC Architectures 24

5.3 2DDWT Architectures 28

5.3.1 Row Processor 30

5.3.2 Column Processor 38

5.4 Power Design Consideration 46

5.4.1 Clock Gating 46

5.4.2 Clock Gating Register 50

CHAPTER 6

EXPERIMENTAL RESULT AND DISCUSS 53

6.1 Library Preparation 53

6.2 Experimental Result 60

6.3 Discussion 65

CHAPTER 7

CONCLUSIONS 67

REFERENCE 68

參考文獻 REFERENCE



[1] D. A. Johns and K. Martin, “ Analog Integrated Circuit Design, ” John Wiley & Sons, New York, 1997.

[2] Behzad Razavi, “Design of Analog CCMOS Integrated Circuit, ” McGraw-Hill, Boston, 2001.

[3] C. Sandner, M. Clara, A. Santner, T. Hartig, and F. Kuttner, “A 6-bit 1.2-GS/s low-power flash-ADC in 0.13-μm digital CMOS,” IEEE J. Solid-State Circuits, vol. 40, no. 7, pp. 1499–1505, Jul. 2005.

[4] Kale, A.,V., Palsodkar, P., Dakhole, P.K., “Comparative Analysis of 6 Bit Thermometer-to-Binary Decoders for Flash Analog-to-Digital Converter,” IEEE International Conference on Communication Systems and Network Technologies (CSNT), pp. 543—546, 2012.

[5] Cho, S., H., Lee, C. K., Lee, S., G., Ryu, S., T. “ A Two-Channel Asynchronous SAR ADC With Metastable-Then-Set Algorithm. ” IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 20 , Iss. 4, pp. 765—769, 2012.

[6] Signore, B., P., Kerth, D., A., Sooch, N., Swanson E.S. G. Mallat, “Amonolithic 20-b delta-sigma A/D converter,” IEEE J. Solid-State Circuits, vol. 25, pp. 1311-1317, 1990.

[7] K. Kusumoto, A. Matsuzawa, and K. Murata, “A 10-b 20-MHz 30-mW pipelined interpolating CMOS ADC,” IEEE J. Solid-State Circuits, vol. 28, no. 12, pp. 1200–1206, Dec. 1993.

[8] B. Verbruggen, J. Craninckx, M. Kuijk, P. Wambacq, and G. V. der Plas, “A 2.6 mW 6 bit 2.2 GS/s fully dynamic pipeline ADC in 40-μnm Digital CMOS,” IEEE J. Solid-State Circuits, vol. 45, no. 10, pp. 2080–2090, Oct. 2010.

[9] S. G. Mallat, “A theory for multiresolution signal decomposition: the wavelet representation, ” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 11, pp. 674-693, 1989.

[10] Jo Yew Tham, Lixin Shen, Seng Luan Lee, Hwee Huat Tan, “A general approach for analysis and application of discrete multi-wavelet transforms”, IEEE Transactions on Signal Processing, vol. 48, issue: 2, pp. 457-464, 2000.

[11] Vattikuti Naga Prudhvi Raj, Tad Venkateswarlu, “Denoising of Medical Images Using Undecimated Wavelet Transform”, IEEE International Conference on Recent Advances in Intelligent Computational Systems (RAICS), pp. 483 –-488, 2011.

[12] Md. Rezwanul Ahsan, Muhammad Ibn Ibrahimy, Othman Omran Khalifa, “VHDL Modelling of Fixed-point DWT for the Purpose of EMG Signal Denoising ”, IEEE Third International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN) , pp. 483 -488, 2011.

[13] Vattikuti Naga Prudhvi Raj, Tad Venkateswarlu, “ECG Signal Denoising Using Undecimated Wavelet Transform”, IEEE 3rd International Conference on Electronics Computer Technology (ICECT), pp. 94 -98 , 2011.

[14] Laurent Brechet, Marie-Françoise Lucas, Christian Doncarli, Dario Farina, “Compression of Biomedical Signals With Mother Wavelet Optimization and Best-Basis Wavelet Packet Selection”, IEEE Transactions on Biomedical Engineering , vol.54, pp. 2186 – 2192, 2007.

[15] Eric J. Balster, Benjamin T. Fortener, William F. Turri, “Integer Computation of Lossy JPEG2000 Compression”, IEEE Transactions on Image Processing, vol. 20, pp. 2386 - 2391, 2011.

[16] Mallat, “Multifrequency Channel Decompositions of Images and Wavelet Models,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, pp.2091-2110, 1989.

[17] Mohan Vishwanath, Robert Michael Owens, Mary Jane Irwin, “VLSI Architectures for the Discrete Wavelet Transform”, IEEE Transactions on Circuits and Systems, vol. 42, no. 5, pp. 305-316, 1995.

[18] Aleksander Grzeszczak, Mrinal K. Mandal, Sethuraman Panchanathan, Tet Yeap, “VLSI Implementation of Discrete Wavelet Transform”, IEEE Transactions on VLSI Systems, vol. 4, pp. 421-433, Dec. 1996.

[19] Keshab K. Parhi, Takao Nishitani, “VLSI Architectures for Discrete Wavelet Transforms”, IEEE Transactions on VLSI Systems, vol. 1, no. 2, pp. 191-202, 1993.

[20] Francescomaria Marino, David Guevorkian, Jaakko T. Astola, “Highly Efficient High- Speed/Low-Power Architectures for the 1-D Discrete Wavelet Transform”, IEEE Transactions on Circuits and Systems-Part II, vol. 47, no. 12, pp. 1492-1502, 2000.

[21] W. Sweldens, “The new philosophy in biorthogonal wavelet constructions,” Proc. SPIE, vol. 2569, pp. 68–79, 1995.

[22] I. Daubechies and W. Sweldens, “Factoring wavelet transforms into lifting steps”, Journal of Fourier Analysis and Applications, vol. 4, p247 – 269, 1998.

[23] Pei-Yin Chen, “VLSI implementation for one-dimensional multilevel lifting-based wavelet transform”, IEEE Transactions on Computers, vol. 53, no. 4, pp. 386-398, April, 2004.

[24] Kishore Andra, Chaitali Chakrabarti, Tinku Acharya, “A VLSI Architecture for Lifting-based Forward and Inverse Wavelet Transform”, IEEE Transactions on Signal Processing, vol. 50, no. 4, pp. 966-977, 2002

[25] Chao-Tsung Huang, Po-Chih Tseng, Liang-Gee Chen, “Efficient VLSI Architectures of Lifting-Based Discrete Wavelet Transform by Systematic Design Method”, Proceeding(s) of IEEE international Symposium on Circuits and System, vol. 5, pp.565-568, 2002.

[26] C.-T. Huang, P.-C. Tseng, and L.-G. Chen, “Generic RAM-based architectures for two-dimensional discrete wavelet transform with line-based method,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 15, no. 7, pp. 910-919, July 2005.

[27] B.-F. Wu, and C.-F. Lin, “A high-performance and memory-efficient pipeline architecture for the 5/3 and 9/7 discrete wavelet transform of JPEG2000 codec,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 15, no. 12, pp. 1615-1628, December 2005. (Hsia 26)

[28] Y.-K Lai., L.-F. Lien, and Y.-C. Shih, “A high-performance and memory-efficient VLSI architecture with parallel scanning method for 2-D lifting-based discrete wavelet transform, ” Consumer Electronics, IEEE Transactions on, vol. 55, pp. 400-407, 2009.

[29] K. Andra, C. Chakrabarti, and T. Acharya, “A VLSI architecture for lifting-based forward and inverse wavelet transform,” IEEE Trans. on Signal Processing, vol. 50, no. 4, pp. 966-977, April 2002.

[30] W. Jiang and A. Ortega, “Lifting factorization-based discrete wavelet transform architecture design, ” IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 5, pp. 651–657, May 2001.

[31] H. Liao, M. K. Mandal, and B. F. Cockburn, “Efficient architectures for 1-D and 2-D lifting-based wavelet transforms,” IEEE Trans. on Signal Process., vol. 52, no. 5, pp. 1315–1326, May 2004.

[32] C.-Y. Xiong, J. Tian, and J. Liu, “Efficient high-speed/low-powerline-based architecture for two-dimensional discrete wavelet transform using lifting scheme,” Circuits and Systems for Video Technology, IEEE Transactions on, vol. 16, pp. 309-316, 2006

[33] P.-Y. Chen, “VLSI implementation of lifting discrete wavelet transform using the 5/3 filter”, IEICE Trans. on Information and Systems, vol. E85-D, no. 12, pp. 1893-1897, December 2002.

[34] C.-Y. Xiong, J. Tian, and J. Liu, “Efficient Architectures for Two-Dimensional Discrete Wavelet Transform Using Lifting Scheme, ” Image Processing, IEEE Transactions on, vol. 16, pp. 607-614, 2007.

[35] G.-C. Jung and S.-M. Park, “VLSI implement of lifting wavelet transform of JPEG2000 with efficient RPA (recursive pyramid algorithm) realization,” IEICE Trans. on Fundamentals, vol. E88-A, no. 12, pp. 3508-3515, December 2005.

[36] W. Zhang, Z. Jiang, Z. Gao, and Y. Liu, “An Efficient VLSI Architecture for Lifting-Based Discrete Wavelet Transform, ” Circuits and Systems II: Express Briefs, IEEE Transactions on, vol. 59, pp. 158-162, 2012.

[37] X. Tian, L. Wu, Y.-H. Tan, and J.-W. Tian, “fficient Multi-Input/Multi-Output VLSI Architecture for Two-Dimensional Lifting-Based Discrete Wavelet Transform”, Computers, IEEE Transactions on, vol. 60, pp. 1207-1211, 2011.

[38] Walter Aloisi and Rosario Mita, “Gated-Clock Design of Linear-Feedback Shift Registers, ” IEEE Transactions on Circuits and Systems II: Express Briefs, , vol. 55, pp. 546-550, 2008.

[39] R. S. Katti, X. Ruan, and H. Khattri, “Multiple-Output low-power linean feedback shift register design,” IEEE Transactions on Circuits and Systems I, Reg. Papers, vol. 53, no. 7, pp. 1487–1495, Jul. 2006.

[40] M. Lowy, “Parallel implementation of linear feedback shift register for low power applications,” IEEE Transactions on Circuits and Systems II, Analog Digit. Signal Process., vol. 43, no. 6, Jun. 1996.

[41] Roman Garnett, Timothy Huegerich, Charles Chui, and Wenjie He, “ A Universal Noise Removal Algorithm With an Impulse Detector ”, IEEE Transactions on Image Processing, Vol. 14, Issue 11, pp. 1747-1754, Nov. 2005.

指導教授 蔡宗漢(Tsung-Han Tsai) 審核日期 2015-8-27
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明