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Adaptive data hiding for vector quantization images based on overlapping codeword clustering 总被引:1,自引:0,他引:1
Yen-Shing Tsai 《Information Sciences》2011,181(15):3188-3198
In this paper, an overlapping codeword clustering based data hiding scheme is presented. In this scheme, a mapping table is designed to determine the overlapping codeword clustering and to indicate the index modification in the secret embedding. The mapping table explores the relationship among the sub-codebook’s size, the codeword’s order and the embedding secret message to which the codeword overlapping in sub-codebooks with different sizes is permitted. In addition, the secret embedding is also determined according to the mapping table.The experimental results showed that the number of partitioned sub-codebooks was increased significantly. The average hiding capacity was about 30 K bits while the average embedding distortion was about 1.2 dB. In comparison to similar methods, the proposed scheme provided a larger hiding capacity than others while preserving a similar stego-image quality. Furthermore, the proposed scheme offered a better proportion of hiding compared to image distortion. 相似文献
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矢量量化技术是一种高效和有竞争力的数据压缩方法,但由于其编解码过程中需要较大的计算量影响了其使用。提出了一种改进的基于子矢量特征值的码字快速搜索算法。算法充分利用矢量的3个特征值即和值、子矢量和值以及方差,建立起一种5步码字排除法,使得算法能够快速排除大部分不匹配码字,实现减少计算量的目的。仿真实验结果表明,算法的计算量要小于ZhiBin算法、Pan算法以及Chen算法,证明了改进算法的有效性。 相似文献
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Multimedia Tools and Applications - In this paper, a hyperspectral image compression method is proposed. It is based on spectral clustering, linear prediction and the vector quantization (VQ).... 相似文献
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George E. Tsekouras Mamalis Antonios Christos Anagnostopoulos Damianos Gavalas Dafne Economou 《Information Sciences》2008,178(20):3895-3907
In this paper, we develop a batch fuzzy learning vector quantization algorithm that attempts to solve certain problems related to the implementation of fuzzy clustering in image compression. The algorithm’s structure encompasses two basic components. First, a modified objective function of the fuzzy c-means method is reformulated and then is minimized by means of an iterative gradient-descent procedure. Second, the overall training procedure is equipped with a systematic strategy for the transition from fuzzy mode, where each training vector is assigned to more than one codebook vectors, to crisp mode, where each training vector is assigned to only one codebook vector. The algorithm is fast and easy to implement. Finally, the simulation results show that the method is efficient and appears to be insensitive to the selection of the fuzziness parameter. 相似文献
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针对高光谱影像光谱维的数据量大、传统影像压缩方法不易于保存光谱内信息的特点,对矢量量化数据压缩方法中码书设计和码字搜索两个关键技术进行详细地研究,提出针对高光谱影像压缩的改进方法,并在此基础上实现了对高光谱影像的矢量量化压缩算法。最后通过对不同波段组合的AVIRIS的高光谱数据的实验,从压缩后的压缩率、速率和失真率等方面进行观察和对比,证明矢量量化压缩算法对高光谱影像具有显著的压缩效果。 相似文献
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提出一种基于图像块动态调整的码字内再匹配矢量量化方法。该方法在编码前,首先分析待编码子图像与其八邻域子图像的相似性,通过给定的阈值判断是否相似,如果相似,则用同一个码字编码;否则就单独编码。在编码时,由于匹配码字只是和子图像整体上失真度最小,所以进一步把子图像和匹配码字划分为小块,然后子图像中的每一小块在匹配码字中再匹配。实验结果表明,相对于普通矢量量化,该方法不但可以提高编码速度,而且图像质量也有明显改善。 相似文献
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Yu-Chen Hu Author Vitae 《Pattern recognition》2006,39(9):1715-1724
A novel grayscale image hiding scheme that is capable of hiding multiple secret images into a host image of the same size is proposed in this paper. The secret images to be hidden are first compressed by vector quantization with additional index compression process. Then, the compressed secret images are encrypted and embedded into the least-significant bits of the host pixels. To provide good image quality of the stego-image, the modulus function and the image property are employed to hide the secret bits into the host pixels and determine the number of hidden bits in each host pixel, respectively. According to the results, the proposed scheme provides a higher hiding capacity and a higher degree of security than that of the virtual image cryptosystem. 相似文献
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Fuzzy algorithms for learning vector quantization 总被引:14,自引:0,他引:14
This paper presents the development of fuzzy algorithms for learning vector quantization (FALVQ). These algorithms are derived by minimizing the weighted sum of the squared Euclidean distances between an input vector, which represents a feature vector, and the weight vectors of a competitive learning vector quantization (LVQ) network, which represent the prototypes. This formulation leads to competitive algorithms, which allow each input vector to attract all prototypes. The strength of attraction between each input and the prototypes is determined by a set of membership functions, which can be selected on the basis of specific criteria. A gradient-descent-based learning rule is derived for a general class of admissible membership functions which satisfy certain properties. The FALVQ 1, FALVQ 2, and FALVQ 3 families of algorithms are developed by selecting admissible membership functions with different properties. The proposed algorithms are tested and evaluated using the IRIS data set. The efficiency of the proposed algorithms is also illustrated by their use in codebook design required for image compression based on vector quantization. 相似文献
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Multimedia Tools and Applications - A novel semantic compression based on vector quantization (VQ) and data hiding is proposed. A compact version of the original image is generated, and then, VQ... 相似文献
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《Expert systems with applications》2007,32(1):213-222
This article develops an evolutional fuzzy particle swarm optimization (FPSO) learning algorithm to self extract the near optimum codebook of vector quantization (VQ) for carrying on image compression. The fuzzy particle swarm optimization vector quantization (FPSOVQ) learning schemes, combined advantages of the adaptive fuzzy inference method (FIM), the simple VQ concept and the efficient particle swarm optimization (PSO), are considered at the same time to automatically create near optimum codebook to achieve the application of image compression. The FIM is known as a soft decision to measure the relational grade for a given sequence. In our research, the FIM is applied to determine the similar grade between the codebook and the original image patterns. In spite of popular usage of Linde–Buzo–Grey (LBG) algorithm, the powerful evolutional PSO learning algorithm is taken to optimize the fuzzy inference system, which is used to extract appropriate codebooks for compressing several input testing grey-level images. The proposed FPSOVQ learning scheme compared with LBG based VQ learning method is presented to demonstrate its great result in several real image compression examples. 相似文献
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In this paper an adaptive hierarchical algorithm of vector quantization for image coding is proposed. First the basic codebook is generated adaptively, then the codes are coded into higher-level codes by creating an index codebook using the redundance presented in the codes. This hierarchical scheme lowers the bit rate significantly and causes little more computation and no more distortion than the single-layer adaptive VQ algorithm does which is used to create the basic codebook. 相似文献
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Stanley C. Ahalt Prakoon Chen Cheng-Taou Chou Tzyy-Ping Jung 《The Journal of supercomputing》1992,5(4):307-330
We describe an implementation of a vector quantization codebook design algorithm based on the frequencysensitive competitive learning artificial neural network. The implementation, designed for use on high-performance computers, employs both multitasking and vectorization techniques. A C version of the algorithm tested on a CRAY Y-MP8/864 is discussed. We show how the implementation can be used to perform vector quantization, and demonstrate its use in compressing digital video image data. Two images are used, with various size codebooks, to test the performance of the implementation. The results show that the supercomputer techniques employed have significantly decreased the total execution time without affecting vector quantization performance.This work was supported by a Cray University Research Award and by NASA Lewis research grant number NAG3-1164. 相似文献
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颜色量化(CQ)是减少图像颜色数量的过程,已广泛用于图像压缩。基于八叉树的颜色量化(OCQ)因其编码效率高、内存使用低和调色板选择效果良好而被认为是最流行的CQ算法之一。然而,OCQ应用的一个严峻挑战是如何有效地管理关键的本地颜色。提出了一种基于分块的自适应八叉树颜色量化(AB-OCQ)算法,实验结果表明,与传统的OCQ算法相比,由于增加了对局部颜色的适当处理,AB-OCQ可以显著提高图像质量。在图像压缩比方面,AB-OCQ的综合性能也优于OCQ的。同时,和主流图像文件格式相比,AB-OCQ算法可以在保持压缩的前提下拥有随机访问图像像素数据的特性,该特性能让应用程序在同等内存下存储更多的图像数据,为提高应用程序的效率提供了一种方法。 相似文献
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针对反向传播神经网络(BP-NN)在图像识别运算过程中容易陷入局部极小值的问题,提出了在常规的遗传算法(GA)中引入3个邻域的链式竞争,进行特征选择的图像识别方法.仿真结果表明:将引入链式竞争策略的遗传算法应用到反向传播神经网络中,可以使图像更清晰,提高了图像识别的容错性及效果. 相似文献
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鉴于经典的LBG码书设计算法易陷入局部最优解,首次采用粒子群优化算法来设计图像矢量量化的最优码书,并提出了粒子群矢量量化(PSO-VQ)算法和粒子一致性操作(PCO)。在PSO-VQ算法中,每个粒子表示一个码书,以粒子群进化的方式对初始码书进行迭代而获得最优码书,PCO操作对各初始码书中的码矢量按其灰度均值排序,使不同码书的内部结构基于码矢量灰度均值达到基本一致,确保了结果向全局最优解收敛。实验证明,PSO-VQ算法在解码图像的PSNR值和主观效果上都优于LBG算法,同时拓展了粒子群优化算法的应用领域。 相似文献