A path optional lossless data hiding scheme based on VQ joint neighboring coding

Data hiding is an important technique for covert communication that embeds secret data into a cover image with minimal perceptible degradation. Lossless data hiding is a special type of data hiding technique that guarantees not only the secret data but the cover media can be reconstructed without any distortion. In this paper, a novel path optional lossless data hiding scheme based on the joint neighboring coding (JNC) of the vector quantization (VQ) index table is proposed. The proposed scheme generates a VQ index table based on the cover image first. Next, according to an initial key and secret data content, different adjacent indices may be chosen to perform joint neighboring coding for each index and hide secret data. Finally, an appropriate output codestream is generated based on the minimal length principle. Our main contributions lie in three aspects: (1) the method combines the novel path_based shift method with the traditional JNC method to improve the capacity and stego image quality simultaneously. (2) The secret data extraction and cover image recovering processes are separated and both can be publicized to users. (3) The method is path optional to meet various users’ requirements. To testify the superiority of the proposed method, we compare it with the side match VQ (SMVQ)-based and modified fast correlation VQ (MFCVQ)-based algorithms. According to the experimental results, the proposed scheme outperforms the SMVQ-based and MFCVQ-based algorithms in four aspects, i.e., hiding capacity, stego image quality, transmission efficiency and security level.     

Buffer management for lossless service in shared buffer switches

Fair scheduling and buffer management are two typical approaches to provide differentiated service. Fair scheduling algorithms usually need to keep a separate queue and maintain associated state variables for each incoming flow, which makes them difficult to operate and scale. On the contrary, buffer management (in conjunction with FIFO scheduling) needs only a constant amount of state information and processing, and can be efficiently implemented. In this paper, we consider using buffer management to provide lossless service for guaranteed performance flows in shared buffer switches. We study the buffer size requirement and buffer allocation strategies by starting with the single output switch and then extending the analytical results to the general multiple output switch. We present a universally applicable buffer allocation method for assuring lossless service, and validate the correctness of the theoretical results through simulations.     

基于位平面无损压缩的密文域可逆信息隐藏

针对密文域可逆信息隐藏算法中嵌入率不高,可逆性不强,鲁棒性差的问题,提出一种密文图像位平面无损压缩的可逆信息隐藏算法。首先介绍二进制数据位压缩编码方式,使用该方式将低位平面信息存储于压缩后的高位平面中。而后加密图像,采用比特替换的方式在低位平面嵌入秘密信息,最后按位重组图像。接收方提取秘密信息和恢复图像的操作相互独立。实验证明,该算法具有较高的嵌入率,可逆恢复的载体图像质量较好,能够有效抵抗一定程度的噪声及数据丢失攻击。     

基于小波变换和算术编码的无损图像压缩方法研究

为了提高图像压缩的性能以便实现更好的无损图像压缩,提出了一种基于小波变换和算术编码的无损图像压缩方法。首先,该方法对图像的所有高频和低频分量进行整数小波变换。然后利用期望最大化算法和最大似然估计对几何分布有限混合模型的参数进行了估计。最后结合直方图截断方法完成算术编码。多组图像数据的测试结果显示相比于其他方法,提出压缩方法表现出较好的压缩性能(主观和客观保真度指标),即更高的压缩比和峰值信噪比。     

A lossless compression algorithm of remote sensing image for space applications

A simple and adaptive lossless compression algorithm is proposed for remote sensing image compression, which includes integer wavelet transform and the Rice entropy coder. By analyzing the probability distribution of integer wavelet transform coefficients and the characteristics of Rice entropy coder, the divide and rule method is used for high-frequency sub-bands and low-frequency one. High-frequency sub-bands are coded by the Rice entropy coder, and low-frequency coefficients are predicted before coding. The role of predictor is to map the low-frequency coefficients into symbols suitable for the entropy coding. Experimental results show that the average Comprcssion Ratio （CR） of our approach is about two, which is close to that of JPEG 2000. The algorithm is simple and easy to be implemented in hardware. Moreover, it has the merits of adaptability, and independent data packet. So the algorithm can adapt to space lossless compression applications.     

整系数预测技术在无损音频压缩中的应用

通过对AudioPak音频编码器的分析研究,本文提出了一种改进型的整系数预测技术,AudioPak只是改进型预测算法的特例。改进型整系数预测算法在频响性能上弥补了AudioPak的不足,减少了预测误差的动态范围;在预测误差均值、频谱分布、帧方差等指标方面都有不同程度的提高,从而明确了改进型预测算法的优势。     

Non-separable lifting scheme with adaptive update step for still and stereo image coding

Many existing works related to lossy-to-lossless multiresolution image compression are based on the lifting concept. It is worth noting that a separable lifting scheme may not appear very efficient to cope with the 2D characteristics of edges which are neither horizontal nor vertical. In this paper, we propose to use 2D non-separable lifting schemes that still enable progressive reconstruction and exact decoding of images. Their relevant advantage is to yield a tractable optimization of all the involved decomposition operators. More precisely, we design the prediction operators by minimizing the variance of the detail coefficients. Concerning the update filters, we propose a new optimization criterion which aims at reducing the inherent aliasing artifacts. A theoretical analysis of the proposed method is conducted in terms of the adaptation criterion considered in the optimization of the update filter. Simulations carried out on still images and residual ones generated from stereo pairs show the benefits which can be drawn from the proposed optimization of the lifting operators.     

可逆双正交小波变换在图象压缩中的应用

本文的重点在于研究双正交小波变换在图象压缩中的应用,分析了浮点型滤波器在无失真压缩中的可行性,同时通过对小波变换和边界问题进行的具体分析,提供了该小波变换的另一种算法,使之适合于快速的,渐进性的直至无失真的图象压缩。     

基于D^2PCM的数字减影图象序列无损压缩算法

充分利用数字减影（ＤＳＡ）图象序列在时间域上的减影图象之间仍然存在一定的相似性,提出了一种基于二阶差分ＰＣＭ（Ｄ＾２ＰＣＭ）的编码方式。方法在空间坐标与时间坐标上构成了一个二阶差分,能够有效地减少图象在空间以及时间域上的冗余度,从而实现对ＤＳＡ序列的无损压缩,减少了存储空间与传输时间。实际应用证明该处法是稳定和实用的。     

基于感知器的遥感图像无损压缩编码

无损压缩在遥感领域有极其重要的作用。该文提出一种基于感知器模型的遥感图像无损压缩编码方法,该方法利用感知器具有学习能力的特点,自适应地调整图像的预测系数,对遥感图像进行空间和谱间去相关,然后进行熵编码。实验表明,对于多波段的遥感图像,该方法的压缩效果明显优于无损JPEG(Joint of Picture Expert Group)最优预测模式。