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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 陳文進(Wen-Chin Chen) | |
dc.contributor.author | Sheng-Yen Lin | en |
dc.contributor.author | 林聖晏 | zh_TW |
dc.date.accessioned | 2021-06-17T01:48:48Z | - |
dc.date.available | 2017-07-28 | |
dc.date.copyright | 2017-07-28 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017-07-25 | |
dc.identifier.citation | [1] D. Slepian and J. Wolf, “Noiseless coding of correlated information sources,” IEEE Trans. Inf. Theory, vol. 19, no. 4, pp. 471-480, Jul. 1973.
[2] M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process., vol. 52, no. 10, pp. 2992-3006, Oct. 2004. [3] D. Schonberg, S. C. Draper and K. Ramchandran, “On blind compression of encrypted data approaching the source entropy rate,” in 13th European Signal Process. Conf., pp. 1-4, Sept. 2005. [4] R. Lazzeretti and M. Barni, “Lossless compression of encrypted grey-level and color images,” in 16th European Signal Process. Conf., pp. 1-5, Aug. 2008. [5] A. Kumar and A. Makur, “Distributed source coding based encryption and lossless compression of gray scale and color images,” in 10th IEEE Workshop on Multimedia Signal Process., pp. 760-764, Oct. 2008. [6] W. Liu, W. Zeng, L. Dong and Q. Yao, “Efficient compression of encrypted grayscale images,” IEEE Trans. Image Process. Vol.19, no. 4, pp. 1097-1102, Apr. 2010. [7] W.-F. Jiang, J.-L. Wu, “A distributed source coding based encrypted graylevel image lossless compression method,” master Thesis, Graduate Institute of Networking and Multimedia, National Taiwan University, July, 2015. [8] A. Kumar and A. Makur, “Lossy compression of encrypted image by compressive sensing technique,” in IEEE Region 10 Conf., pp.1-5, Jan. 2009. [9] X. Zhang, Y. Ren, G. Feng and Z. Qian, “Compressing encrypted image using compressive sensing,” in 7th Int. Conf. Intelligent Info. Hiding and Multimedia Signal Process. (IIH-MSP), Oct. 2011. [10] X. Zhang, “Lossy compression and iterative reconstruction for encrypted image,” IEEE Trans. Info. Forensics and Security, vol. 6 no. 1, pp. 53-58, Mar. 2011. [11] X. Zhang, Y. Ren, L. Shen, Z. Qian and G. Feng, “Compressing encrypted images with auxiliary information,” IEEE Trans. Multimedia, vol. 16, no. 5, pp. 1327-1336, Aug. 2014. [12] J. Zhou, X. Liu, O. Au and Y. Tang, “Designing an efficient image encryption-then-compression system via prediction error clustering and random permutation,” IEEE Trans. Info. Forensics and Security, vol. 9, no. 1, pp. 39-50, Jan. 2014. [13] J. Zhou, O. Au, G. Zhai, Y. Tang and X. Liu, “Scalable compression of stream cipher encrypted images through context-adaptive sampling,” IEEE Trans. Info. Forensics and Security, vol. 9, no.11, pp. 1857-1868, Nov. 2014. [14] D. Varodayan, A. Aaron and B. Girod, “Rate-adaptive codes for distributed source coding,” EURASIP Signal Process. Journal, Special Section on Distributed Source Coding, vol. 86, no.11, pp. 3123-3130, Nov. 2006. [15] A. Liveris, Z. Xiong and C. Georgpiades, “Compression of binary sources with side information at the decoder using LDPC codes,” IEEE Commun. Lett., vol. 6, no. 10, pp. 440-442, 2002. [16] X. Artigas, J. Ascenso, M. Dalai, S. Klomp, D. Kubasov and M. Ouaret, “The discover codec: Architecture, techniques and evaluation,” Picture Coding Symposium, Nov, 2007. [17] Y.-S. Pai, H.-P. Cheng and J.-L. Wu, “Fast decoding for LDPC based distributed video coding,” ACM Int. Conf. Multimedia, pp. 1211-1214, Oct. 2010. [18] Computer Unified Device Architecture (CUDA): http://developer.nvidia.com/object/cuda.html. [19] T.-C. Su, Y.-C. Shen and J.-L. Wu, “Real-time decoding for LDPC based distributed video coding,” ACM Int. Conf. Multimedia, pp. 1261-1264, Nov. 2011. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/67769 | - |
dc.description.abstract | 加密影像的無失真壓縮可以透過 Slepian-Wolf 編碼來達成,而壓縮率會與解碼時如何有效利用資料的相依性有密切的相關。這篇論文為了提高壓縮率,我們從先前已解碼的子影像來預估當前欲解碼子影像上的統計資訊,並利用已解碼的位元平面做進一步精準化。此外,我們提出並實現了一種基於 LDPCA 編碼的高效能無失真壓縮方法。由於LDPCA 解碼的運算程序極其複雜,且為整個系統中最耗時的部分,因此我們使用 CUDA 架構,針對 LDPCA 中的 sum-product 演算法提出一個平行化的設計。為避免運算資源浪費在不必要的運算上,本論文另外提出收斂偵測機制。實驗結果顯示,與先前使用Slepian-Wolf編碼的無損壓縮方案相比,壓縮率可以提高百分之七,且平行化的 LDPCA 解碼器的解碼執行時間比循序的LDPCA解碼器快了約40倍。 | zh_TW |
dc.description.abstract | Lossless compression of encrypted images can be achieved through Slepian-Wolf (SW) coding, and the compression performance is highly related to how data dependency is exploited while decoding. In this thesis, to improve the compression performance, the statistics of current decoded subimage is estimated from the previous decoded subimages in the same resolution level and then is further refined by the decoded bit planes. Besides, an efficient approach for lossless compressing encrypted images, on the basis of the low-density parity-check accumulate (LDPCA) codes, is proposed and realized. Due to the intricate procedures, LDPCA decoding is the most time-consuming task in our scheme. As a result, a parallelized sum-product algorithm for LDPCA decoding based on CUDA is designed, and an early jump out detection mechanism is also proposed to avoid wasting computational resources on unnecessary operations. Experiment results show that the compression performance is improved about 7% in average, as compared with the state-of-the-art lossless compression scheme using SW coding, and the decoding time using parallel LDPCA decoder is about 40 times faster than the sequential LDPCA decoder. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T01:48:48Z (GMT). No. of bitstreams: 1 ntu-106-R04922116-1.pdf: 2798531 bytes, checksum: c78f20c708d6ed613a0b9e2e50636b2a (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | 口試委員審定書 ii
誌謝 iii 中文摘要 iv Abstract v Contents vi List of Figures viii List of Tables xi Chapter 1 Introduction 1 Chapter 2 Related Works 3 2.1 Lossless Compression of Encrypted Images 3 2.2 Lossy Compression of Encrypted Images 4 Chapter 3 Introduce of LDPCA 6 3.1 LDCPA Encoder 7 3.2 LDPCA Decoder 8 3.2.1 LDPC Code Construction 10 3.2.2 Sum-Product Algorithm 12 Chapter 4 Proposed Scheme for Compressing Encrypted Images 15 4.1 Data Sender 16 4.1.1 Decomposition 17 4.1.2 Content-Adaptive Interpolation 19 4.1.3 Light-Weight Preprocessing 21 4.1.4 Encryption 23 4.2 Service Provider (LDPCA Encoder) 24 4.3 Data Receiver and Service Provider (LDPCA Decoder) 26 4.3.1 Variance Estimation 27 4.3.2 Refinement 28 4.3.3 Correlation Noise Modeling and Encryption 29 4.3.4 LDPCA Decoding and Reconstruction 29 Chapter 5 Proposed Efficient Scheme for LDPCA Decoding 30 5.1 The φ Function Pre-Computation 31 5.2 Parallel Reduction in HPK 34 5.3 Early-stop Detection Mechanism 36 Chapter 6 Experiment Results 40 6.1 The Compression Performance of the Proposed Scheme for Compressing Encrypted Images 40 6.2 The Speed-up Ratios of the Proposed Efficient Scheme for LDPCA Decoding 42 Chapter 7 Conclusion and Future Work 45 Bibliography 46 | |
dc.language.iso | en | |
dc.title | 一種基於LDPCA之加密灰階影像高效能無失真壓縮機制 | zh_TW |
dc.title | An Effective LDPCA based Lossless Compression Scheme for Encrypted Gray-level Images | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 吳家麟(Ja-Ling Wu) | |
dc.contributor.oralexamcommittee | 朱威達(Wei-Ta Chu),鄭文皇(Wen-Huang Cheng),胡敏君(Min-Chun Hu) | |
dc.subject.keyword | 加密影像無失真壓縮,Slepian-Wolf 編碼,低密度奇偶校驗碼,總和-乘積演算法,CUDA, | zh_TW |
dc.subject.keyword | lossless compressing encrypted images,Slepian-Wolf coding,low-density parity-check accumulate codes,sum-product algorithm,CUDA, | en |
dc.relation.page | 48 | |
dc.identifier.doi | 10.6342/NTU201702006 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2017-07-26 | |
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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