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A Study of Image Quality Enhancing and Information Hiding Based on Vector Quantization
|關鍵字:||codebook;向量量化;difference map;image compression;information hiding;vector quantization;資訊隱藏;Sobel邊緣偵測;差值表;影像壓縮||出版社:||資訊管理學系所||引用:||Y. Linde, A. Buzo, and R. M. Gray, “An algorithm for vector quantizer design,” IEEE Transactions on Communications, vol. 28, no. 1, pp. 84-95, Jan. 1980. R. M. Gray, “Vector quantization,” IEEE ASSP Magazine, vol. 1, no. 2, pp. 4-29, Apr. 1984. S. Chen, Z. He, and B. L. Luk, “A generic postprocessing technique for image compression,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 4, pp. 546 - 553, Apr. 2001. W. Xu, A. K. Nandi, and J. Zhang, “Novel fuzzy reinforced learning vector quantisation algorithm and its application in image compression,” IEE Proceedings Vision, Image, and Signal Processing, vol. 150, no. 5, Oct. 2003. George E. Tsekouras, “A fuzzy vector quantization approach to image compression,” Applied Mathematics and Computation, vol. 167, no. 1, pp. 539-560, Aug. 2005. R. Lancini and S. 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Sobel, “Neighborhood coding of binary images fast contour following and general array binary processing,” Computer Graphics and Image Processing, vol. 8, no. 1, pp. 127-135, Aug. 1978.||摘要:||
VQ編碼法是失真壓縮之一種，其主要特性為以編碼簿之索引值替代其區塊之向量，在影像還原時只需要將索引值對照至編碼簿內相對應的編碼字，即達到影像壓縮之目的。但也由於VQ編碼法是採用固定區塊編碼及固定的編碼簿大小，故其影像品質被限制在一定的範圍之內。於是本論文提出改善VQ編碼法之影像品質的技術，主要是利用VQ壓縮後之影像與原始影像之差值表做可適應性之編碼，藉此資訊來達到改善影像品質之目的，並且可隨需求將差值表從有失真壓縮調整到無失真壓縮。而在資訊隱藏中，到目前為止已有相當多的reversible的方法被發表出來，其中亦有包括針對Vector Quantization (VQ)壓縮碼所做的資訊隱藏，但以往那些方法多半是單純地將機密資訊藏在裡面，並且會導致影像品質變差，於是本論文提出了一種新的概念，透過原始影像與其VQ解碼影像之差值編碼技術做為改善影像品質之依據，並利用Sobel邊緣偵測找出相對應之區塊索引以控制藏量。本論文不只將機密資訊藏在VQ壓縮碼內，甚至將機密資訊與影像品質的改善結合在一起，藉由藏匿資訊的過程來提升影像品質。實驗結果也顯示，本論文的方法可同時達到資訊隱藏及改善影像品質之目的。
Vector Quantization (VQ) is a kind of lossy compression technique, its characteristic is to use the indices of codebook to replace the block vectors while only comparing the indices corresponding to the codewords of codebook during image recovering. Since Vector Quantization coding uses fixed block coding and fixed size of codebook, the image quality is limited within in a certain range. In this thesis, a technique is proposed to improve VQ image quality. The proposed technique adjusts the encoding of the difference map between the original image and its restored VQ compressed version, thus taking this information to improve the image quality and to adjust the difference map from the lossy compression to lossless compression, according to user''s demand. Recently, several reversible information hiding schemes have been proposed which also included schemes based on vector quantization (VQ) compressed code, but most of those methods just simply hide information internally, leading to a worse image quality. This thesis presents a novel concept which embeds information into VQ compressed code of an image as well as enhancing the decompressed VQ image quality. Moreover, the quality is improved as the embedding capacity is being increased by suitable threshold selected in Sobel detection. The experiments also showed that our method can simultaneously achieve the purposes of information hiding and enhancing image quality.
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