臺灣博碩士論文加值系統

在高品質數位影像處理的應用如數位影像或是影片拍攝、液晶螢幕顯示器處理與醫療影像分析裡，影像對比度增強扮演著一個很重要的角色。為了使高解析度的影像應用可以達到即時影像處理，必須要設計一個有效率的影像增強硬體架構來達到即時影像處理。因此本論文提出了一個新式的硬體導向之對比度增強演算法來有效的實現硬體設計。針對硬體實現的考量，本論文提出近似法來節省演算法裡計算複雜度較高的式子。經由人因測試與數據實驗表示本論文所提出的硬體導向的對比度增強演算法能夠達到良好的影像品質。為了達到硬體及時運算的效能，我們提出了以參數控制為導向之可重組式架構來增進硬體的利用率以及節省電路面積進而降低硬體實現成本。實驗結果表示本論文所提出的硬體導向之影像對比度演算法在影像解析度為1920×1080時能夠達到每秒48.23幅之運算速度，這代表著本論文所提出的硬體架構能夠實現即時數位影像處理系統。

Contrast enhancement is crucial when generating high quality images for image processing applications such as digital image or video photography, LCD processing, and medical image analysis. In order to achieve real-time performance for high-definition video applications, it is necessary to design efficient contrast enhancement hardware architecture to meet the needs of real-time processing. In this paper, we propose a novel hardware-oriented contrast enhancement algorithm which can be implemented effectively for hardware design. In order to be considered for hardware implementation, approximation techniques are proposed to reduce these complex computations during performance of the contrast enhancement algorithm. The proposed hardware-oriented contrast enhancement algorithm achieves good image quality by measuring the results of qualitative and quantitative analyses. To decrease hardware cost and improve hardware utilization for real-time performance, a reduction in circuit area is proposed through use of parameter-controlled reconfigurable architecture. The experiment results show that the proposed hardware-oriented contrast enhancement algorithm can provide an average frame rate of 48.23 fps at high definition resolution 1920×1080. This means that the proposed hardware architecture can run in real-time.

中文摘要 i
ABSTRACT ii
誌謝 iii
CONTENTS iv
LIST OF TABLES v
LIST OF FIGURES vi
Chapter 1 INTRODUCTION 1
Chapter 2 PROPOSED ALGORITHM 4
2.1 Contrast Enhancement Algorithm 4
2.2 Hardware Implementation Consideration 6
2.2.1 Hardware consideration of log_2 k 8
2.2.2 Newton''s Divided Difference Interpolation Formula 8
2.2.3 Hardware consideration of 2^k 9
2.3 Hardware-Efficient Contrast Enhancement Algorithm 10
Chapter 3 HARDWARE ARCHITECTURE DESIGN 12
3.1 Implementation of the ISC module 14
3.2 Implementation of the WDF, SCDF, and AGC modules 14
3.2.1 Implementation of the log_2 k module and 2^k module 14
3.2.2 Implementation of Reconfigurable Structure 15
3.3 Implementation of Half Histogram Design 16
3.4 Implementation of FLT module 16
Chapter 4 EXPERIMENTAL RESULTS 19
4.1 Image Quality Comparison 19
4.1.1 Visual Assessment 19
4.1.2 Comparison 25
4.1.3 Qualitative Evaluation 26
4.2 Specification and FPGA Implementations 27
4.3 Analysis of Hardware Utilization 29
4.4 Analysis of Processing Time Reduction 30
Chapter 5 CONCLUSIONS 31
REFERENCES 32

[1]Tarik Arici, Salih Dikbas and Yucel Altunbasak, “ A Histogram Modification Framework and Its Application for Image Contrast Enhancement, ” IEEE Trans. Image Processing., vol. 18, no. 9, pp. 1921-1935, 2009.
[2]N. Chang, I. Choi and H. Shim, “ DLS: dynamic backlight luminance scaling of liquid crystal display, ” IEEE Trans. Systems, Very Large Scale Integration (VLSI) Systems,., vol. 12, no. 8, pp. 837-846, 2004.
[3]J.-Y. Kim, L.-S. Kim and S.-H. Hwang, “ An advanced contrast enhancement using partially overlapped sub-block histogram equalization, ” IEEE Trans. Circuits and Systems for Video Technology., vol. 11, no. 4, pp. 475-484, 2001.
[4]J.-L. Starck, Fionn Murtagh, Emmanuel J. Cands, and David L. Donoho, “ Gray and color image contrast enhancement by the curvelet transform, ” IEEE Trans. Image Processing., vol. 12, no. 6, pp. 706-717, 2003.
[5]J. Alex Stark, “ Adaptive image contrast enhancement using generalizations of histogram equalization, ” IEEE Trans. Image Processing., vol. 9, no. 9, pp. 889-896, 2000.
[6]H.R. Sheikh, and A.C. Bovik, “ Image information and visual quality, ” IEEE Trans. Image Processing., vol. 15, no. 2, pp. 430-444, 2006.
[7]M. Hanmandlu, O.P. Verma, N.K. Kumar, and M. Kulkarni, “A Novel Optimal Fuzzy System for Color Image Enhancement Using Bacterial Foraging, ” IEEE Trans. Instru. and Measure., vol. 58, no. 8, pp. 2867-2879, 2009.
[8]K. Panetta, S.Agaian, Yicong Zhou and E.J. Wharton, “ Parameterized Logarithmic Framework for Image Enhancement, ” IEEE Trans. Systems, Man, and Cybernetics., vol. 41, no. 2, pp. 460-473, 2011.
[9]W.-C. Chen, S.-C. Huang and T.-Y. Lee, “An efficient Reconfigurable Architecture Design and Implementation of Image Contrast Enhancement Algorithm,” IEEE Int. Conf. Embedded software and systems, 2012.
[10]S. Agaian, K. Panetta, and A. Grigoryan, “Transform-based image enhancement algorithms with performance measure, ” IEEE Trans. Systems, Image Process., vol. 10, no. 3, pp. 367-382, 2001.

[11]Daeyoun Cho, W.-S. Oh and G.-W. Moon, “ A Novel Adaptive Dimming LED Backlight System With Current Compensated X-Y Channel Drivers for LCD TVs, ” IEEE Trans. Display Technology., vol. 7, no. 1, pp. 29-35, 2011.
[12]P.-S. Tsai, C.-K. Liang, T.-H. Huang, and H. H. Chen, “Image enhancement for backlight-scaled TFT-LCD displays,” IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 4, pp. 574-583, Apr. 2009.
[13]F.-C. Lin, Y.-P. Huang, L.-Y. Liao, C.-Y. Liao, H.-P. Shieh, T.-M. Wang and S.-C. Yeh, “ Dynamic Backlight Gamma on High Dynamic Range LCD TVs, ” IEEE Trans. Display Technology., vol. 4, no. 2, pp. 139-146, 2008.
[14]Ali Iranli, Wonbok Lee and Massoud Pedram, “ HVS-Aware Dynamic Backlight Scaling in TFT-LCDs, ” IEEE Trans. Display Technology., vol. 14, no. 10, pp. 1103-1116, 2006.
[15]S. Dockstader and M. Tekalp, “Multiple camera tracking of interacting and occluded human motion,” Proc. IEEE, vol. 89, no. 10, pp. 1441-1455, Oct. 2001.
[16]Y. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Trans. Consum. Electron., vol. 43, no. 1, pp. 1-8, 1997.
[17]Y. Wan, Q. Chen, and B. Zhang, “Image enhancement based on equal area dualistic sub-image histogram equalization method,” IEEE Trans. Consum. Electron., vol. 45, no. 1, pp. 68-75, 1999.
[18]K. S. Sim, C. P. Tso, and Y. Tan, “Recursive sub-image histogram equalization applied to gray-scale images,” Pattern Recognit. Lett., vol. 28, pp. 1209-1221, 2007.
[19]M. Kim and M. G. Chung, “Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement,” IEEE Trans. Consum. Electron., vol. 54, pp. 1389-1397, Aug. 2008.
[20]Y.-S. Chiu, F.-C. Cheng and S.-C. Huang, “Efficient Contrast Enhancement Using Adaptive Gamma Correction and Cumulative Intensity Distribution” IEEE International Conference on Systems, Man, and Cybernetics., pp. 2946-2950, Oct. 2011.