Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19555
標題: 高容量可回復式資訊隱藏法及其在高動態範圍影像編碼法之應用
High Capacity Reversible Data Hiding Scheme and Its Application to HDR Image Coding
作者: 林育如
Lin, Yuju
關鍵字: Reversible data hiding
可回復式資料隱藏
Difference expansion (DE)
Prediction-error expansion
High dynamic range images
Image encoding
差值擴展資料隱藏
預測誤差擴展資料隱藏
高動態範圍影像
影像編碼
出版社: 資訊科學與工程學系所
引用: [1] Zhicheng Ni, Yun-Qing Shi, Nirwan Ansari, and Wei Su, “Reversible data hiding,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354-361, Mar. 2006. [2] J. Tian, “Reversible Data Embedding Using a Difference Expansion,” IEEE Transation on Circuits and Systems for Video Technology, vol.13, No.8, pp.890-896, Aug. 2003. [3] J. Tian and Raymond O. Wells, Jr., “Reversible data-embedding with a hierarchical structure”, Image Processing (ICIP), vol. 5, pp. 24-27, Oct. 2004. [4] L. Kamstra and H. Heijmans, “Reversible data embedding into images using wavelet techniques and sorting,” IEEE Trans. Image Process., vol. 14, no. 12, pp. 2082-2090, Dec. 2005. [5] L. Kamstra and H. Heijmans, “Wavelet techniques for reversible data embedding into images,” Centrum voorWiskunde en Informatica Rep. 2004. [6] D. M. Thodi and J. J. Rodriquez, “Prediction-error-based reversible watermarking,” in Proc. IEEE Conf. Image Processing, Oct. 2004, pp. 1549-1552. [7] ——, “Reversible watermarking by prediction-error expansion,” in Proc. IEEE Southwest Symp. Image Analysis and Interpretation, Mar. 2004, pp. 28-30. [8] ——, “Expansion embedding techniques for reversible watermarking,” IEEE Trans. Image Process., vol. 13, no. 3, pp. 721-730, Mar. 2007. [9] P. E. Debevec and J. Malik, “Recovering High Dynamic Range Radiance Maps from Photographs,” Proceedings of SIGGRAPH ''97, pp. 369-378, Aug. 1997. [10] G. L. Ward, ”The LogLuv Encoding for Full Gamut, High Dynamic Range Images,” Journal of Graphics Tools, vol. 3, No. 1, pp. 15-31, 1998. [11] S. B. Kang, M. Uyttendaele, S. Winder, and R. Szeliski, “High Dynamic Range Video,” ACM. [12] G. L. Ward, ”The Radience Lighting Simulation and Rendering System,” Proceedigs of ACM SIGGRAPH, Orlando, Florida, pp. 459-472, 1994. [13] W. Bender, D. Gruhl, N. Morimoto, and A. Lu, “Techniques for data hiding,” IBM Syst. J., vol. 35, no. 3, pp. 313-336, 1996. [14] J. M. Barton, “Method and apparatus for embedding authentication information within digital data,” U.S. Patent 5 646 997, 1997. [15] C. W. Honsinger, P. Jones, M. Rabbani, and J. C. Stoffel, “Lossless recovery of an original image containing embedded data,” U.S. Patent 6 278 791, 2001. [16] B. Macq, “Lossless multiresolution transform for image authenticating watermarking,” presented at the European Signal Processing Conf., Tampere, Finland, Sep. 2000. [17] J. Fridrich, M. Goljan, and R. Du, “Lossless data embedding—New paradigm in digital watermarking,” EURASIP J. Appl. Signal Process., vol. 2, pp. 185-196, 2003. [18] ——, “Distortion-free data embedding,” in Proc. 4th Information Hiding Workshop, New York, 2001, vol. 2137, pp. 27-41, Lecture Notes Comput. Sci.. [19] ——, “Invertible authentication,” in Proc. SPIE Photonics West, Security and Watermarking of Multimedia Contents III, Jan. 2001, vol. 3971, pp. 197-208. [20] M. U. Celik, G. Sharma, A. M. Tekalp, and E. Saber, “Lossless generalized- LSB data embedding,” IEEE Trans. Image Process., vol. 14, no. 2, pp. 253-266, Feb. 2005. [21] L. Kamstra and H. Heijmans, “Wavelet techniques for reversible data embedding into images,” Centrum voorWiskunde en Informatica Rep. 2004. [22] A. M. Alattar, “Reversible watermark using the difference expansion of a generalized integer transform,” IEEE Trans. Image Process., vol. 13, no. 8, pp. 1147-1156, Aug. 2004. [23] G.. Ward and M. Simmons, “Subband Encoding of High Dynamic Range Imagery,” Proceedings of the first Symp. Applied Perception in Graphics and Visualization (APGV), ACM Press, pp.83-90, 2004. [24] R. Mantiuk, G. Krawczyk, Myszkowski and H. P. Seidel, “Perception Motivated High Dynamic Range Video Encoding,” ACM Transactions on Graphics, vol. 23, No. 3, pp.733-741, 2004. [25] R. Xu, S. N. Pattanaik, and C. E. Hughes, “High-Dynamic Range Still-Image Encoding in JPEG 2000,” IEEE Computer Graphics and Applications, Vol. 25, No.6, pp.57-64, 2005. [26] F. Durand and J. Dorsey, “Fast Bilateral Filtering for The Display of High Dynamic Range Image,” Proceedings of SIGGRAPH '02, pp. 257-265, 2002. [27] The HDR testing images are from: http://www.anyhere.com/gward/hdrenc/pages/originals.html http://gl.ict.usc.edu/HDRShop/
摘要: 資訊隱藏法是一種將保密的資訊隱藏在影像當中的技術,藉由傳送藏有資訊的影像,達到秘密資訊與影像共同傳輸的目的,因此資料隱藏法可以防止影像遭到不當拷貝、鑑定內容的正確性、追蹤散佈情形、監視資訊是否傳播出去等等的一種方法。一般的資訊隱藏法在藏入後,將對影像造成永久性的失真,但對醫學影像、軍事用途影像等是不允許失真的,因此一些學者提出可回復式資訊隱藏法。可回復式資料隱藏法是一種在取出藏入的資訊同時可以完全還原影像的方法。一般來說,資料隱藏法多是利用影像中可被壓縮或量化紀錄的方式,空出一些空間將資訊藏入。我們參考了Tain與Thodi等人的做法,以高度利用影像當中的相關性將資訊藏入,並考慮邊界的預測狀況,提出一個基於邊界預測誤差的高容量可回復式資訊隱藏法。由於所提方法更充份的利用影像像素之間的相關性,因此可以高容量且低失真地將資訊藏入影像。實驗的結果顯示,在藏量小於1bpp的狀況下,比Thodi的方法好1dB。另外,我們以重複性藏入所提的方法,達到高容量的效果,最高藏量可達2.6bpp,比起同樣具有高藏量的Tian所提出的方法,在藏量與影像品質上的數值都較好。 高動態範圍影像是一種能完整包含外界景物的真實亮度的影像格式。目前已有在醫學、攝影、電腦繪圖上面的應用,將很有可能成為下一代的影像格式。然而,高動態範圍影像龐大的檔案格式將對儲存與傳輸產生困難,若能有效的壓縮高動態範圍影像,將有助於此影像格式的應用與發展。目前已有許多學者提出高動態範圍影像的壓縮法,但多不能相容於現有的影像格式,也就是說,必須以特定的軟體開啟觀看。我們運用高容量資訊隱藏來達到高動態範圍影像的壓縮,特點在於壓縮之後的影像格式為一般的低動態範圍影像,使用者可以一般軟體觀看壓縮後的影像,以決定是否還原為高動態範圍影像格式來使用。我們把高動態範圍影像經過色調對應後得到一低動態範圍影像,把原來高動態範圍影像與其相除後即可得到所謂的比例影像(ratio image)。把比例影像經過對數轉換後,再線性對應成每個頻道8位元的影像,以JPEG2000壓縮後,即以所提的高容量可回復式資訊隱藏法將其嵌入低動態範圍影像。當要還原回HDR影像時,就把嵌於低動態範圍影像之比例影像取回,再相乘即可解回原來的HDR影像。所提出的方法有以下兩個優點,(一)編碼後的HDR影像能相容於一般LDR影像處理系統,並可以提供使用者在壓縮的狀態下預覽影像的內容;(二)由於所使用的資訊隱藏法可藏入的資訊量多,適合保留還原用的比例影像,所以還原的HDR影像具有低失真與高品質。
Reversible data hiding enables the embedding of useful information in a host signal without any loss of host information. Tian''s difference-expansion technique is a high-capacity, reversible method for data hiding. Thodi''s proposed a better scheme. His reversible data hiding method use histogram shift technique and prediction-error expansion and have good capacity control mechanism and better exploits the correlation inherent in the neighborhood of a pixel. Although Thodi''s predict method is good, it does not good enough to predict the pixels at edge region. We proposed an edge-based predictor to better predict the edge region and the method has PSNR 1dB higher than Thodi's method. By using the multi-layer embedded method, the proposed method has larger embedding capacity (about 2.4bpp) and better quality of embedded image than Tian's method. The range of luminance values in real world scenes often spans many orders of magnitude, which means capturing those values in a physically meaningful way might require high-dynamic range (HDR) data. Such HDR data is becoming increasingly common and important in surveillance, remote sensing, space research, computer graphics and medical applications. Using the raw size of the HDR image may cause potential problems in regard to storage and transmission, a large quantity of bytes in HDR data is wasted containing perceptually unimportant information and some data redundancy. To address this issue, we propose a novel HDR image encoding algorithm in this study. The encoding algorithm is based on our data hiding method. We first obtain a tone-mapped LDR image from a tone-mapping operator, and then divide the HDR pixels by the tone-mapped luminance to have the ratio image. The ratio image can be encoded by JPEG2000 compression algorithm and then embedded into the tone-mapped LDR image by data hiding. In the decoding phase, we can recover the original HDR image by calculating the product of the reconstructed ratio image and tone-mapped LDR image. The characteristics of the proposed method are summarized as follows: (1) The encoded HDR image is backwards compatible with existing LDR image software; and (2) The restored HDR image has high quality and very low RMSE.
URI: http://hdl.handle.net/11455/19555
其他識別: U0005-2108200823261900
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2108200823261900
Appears in Collections:資訊科學與工程學系所

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