混沌权值变异的Huffman树图像加密算法

提出一种采用混沌权值变异的Huff man树的图像加密算法.此算法在熵编码过程中,以基本的Huffman树为标准,利用双耦合混沌序列1对DC系数进行树的结构未变异、路径值变异的加密;再利用双耦合混沌序列2对AC系数进行码字序号的加密.论文对算法进行了仿真,并对安全性、计算复杂度、压缩比性能进行了分析.实验结果表明,该算法基本上不影响压缩效率,且计算复杂度低、安全性高和实时性好,可用于网络上的图像服务.     

A module-based LSB substitution method with lossless secret data compression

All the various data hiding methods can be simply divided into two types: (1) the extracted important data are lossy, (2) the extracted important data are lossless. The proposed method belongs to the second type. In this paper, a module-based substitution method with lossless secret data compression function is used for concealing smoother area of secret image by modifying fewer pixels in the generated stego-image. Compared with the previous data hiding methods that extract lossless data, the generated stego-image by the proposed method is always with better quality, unless the hidden image is with very strong randomness.     

无损自适应分布式算术编码的研究及应用

目前分布式算术编码研究都是基于先验概率已知的有损压缩,为了实现概率自适应的无损压缩,研究了采用结束字符和概率自适应的编码方式来实现编码,提出了无损自适应分布式算术编码。实验结果表明,该算法拥有更好的压缩效果和更低的解码复杂度,并且在实际应用中,编解码可以同时进行。由于无损自适应分布式算术编码具有编码简单、压缩效果好的优点,故将它和比特面编码结合实现超光谱图像压缩,并将仿真结果与3D-SPECK算法比较,结果表明了该方法可以使信噪比提高0.13-0.37dB。     

A Fast Algorithm for Adaptive Prefix Coding

In this paper we present a new algorithm for adaptive prefix coding. Our algorithm encodes a text S of m symbols in O(m) time, i.e., in O(1) amortized time per symbol. The length of the encoded string is bounded above by (H+1)m+O(nlog ² m) bits where n is the alphabet size and H is the entropy. This is the first algorithm that adaptively encodes a text in O(m) time and achieves an almost optimal bound on the encoding length in the worst case. Besides that, our algorithm does not depend on an explicit code tree traversal. A preliminary version of this paper appeared in the Proceedings of the 2006 IEEE International Symposium on Information Theory (ISIT 2006). M. Karpinski’s work partially supported by a DFG grant, Max-Planck Research Prize, and IST grant 14036 (RAND-APX). Y. Nekrich’s work partially supported by IST grant 14036 (RAND-APX).     

On the implementation of bytecode compression for interpreted languages

This paper describes a new method for code space optimization for interpreted languages called LZW‐CC . The method is based on a well‐known and widely used compression algorithm, LZW , which has been adapted to compress executable program code represented as bytecode. Frequently occurring sequences of bytecode instructions are replaced by shorter encodings for newly generated bytecode instructions. The interpreter for the compressed code is modified to recognize and execute those new instructions. When applied to systems where a copy of the interpreter is supplied with each user program, space is saved not only by compressing the program code but also by automatically removing the unused implementation code from the interpreter. The method's implementation within two compiler systems for the programming languages Haskell and Java is described and implementation issues of interest are presented, notably the recalculations of target jumps and the automated tailoring of the interpreter to program code. Applying LZW‐CC to nhc98 Haskell results in bytecode size reduction by up to 15.23% and executable size reduction by up to 11.9%. Java bytecode is reduced by up to 52%. The impact of compression on execution speed is also discussed; the typical speed penalty for Java programs is between 1.8 and 6.6%, while most compressed Haskell executables run faster than the original. Copyright © 2008 John Wiley & Sons, Ltd.     

COBRA: Compression of the Basis for PCA Represented Animations

In this paper, we present an extension of dynamic mesh compression techniques based on PCA. Such representation allows very compact representation of moving 3D surfaces; however, it requires some side information to be transmitted along with the main data. The biggest part of this information is the PCA basis, and since the data can be encoded very efficiently, the size of the basis cannot be neglected when considering the overall performance of a compression algorithm.
We present a new work in this area, as none of the papers about PCA based compression really addresses this issue. We will show that for an efficient and accurate encoding there are better choices than even sophisticated algorithms such as LPC.
We will present results showing that our approach can reduce the size of the basis by 90% with respect to direct encoding, which can lead to approximately 25% increase of performance of the compression algorithm without any significant loss of accuracy. Such improvement moves the performance of the PCA encoder beyond the performance of current state of the art dynamic mesh compression algorithms, such as the recently adopted MPEG standard, FAMC.     

串脉冲超声导波断轨检测技术研究

针对传统的钢轨断轨检测效率低、无法进行实时检测的不足,对串脉冲超声导波断轨检测方法进行了研究.首先为了增强发射能量,同时达到脉冲叠加的目的,研发了脉冲个数、脉宽、间隔均可调的高压串脉冲超声导波发射系统;为了保证接收信号的信噪比和空间精度,用匹配滤波的方法对接收信号进行脉冲压缩.采用研制的串脉冲超声导波断轨检测系统,选用SH导波换能器在钢轨上进行了检测实验.结果表明,检测系统性能稳定,经过串脉冲叠加,使接收信号的幅值约为单脉冲接收信号的3倍,经过匹配滤波后,信噪比得到明显提升.该方法的换能器置于轨腰,能够对钢轨实现在线监测.     

EZW算法中小波分解层数及扫描次数对图像压缩性能的影响

嵌入式零树小波编码方法(EZW)是目前公认的效率最高的小波图像编码方法之一。 EZW算法中,不同的小波分解层数能够影响小波变换的时频分辨率和小波系数的变化范围,从而影响最终的编码效率;扫描次数的多少直接关系到能被编码的有效小波系数,从而影响最终的编码增益。讨论了 EZW 算法中小波分解层数和小波系数的扫描次数对图像压缩性能的影响,为基于EZW算法的小波图像压缩中的选择合适的小波分解层数及扫描次数提供了参考。通过仿真实验可以看出,在相同的扫描次数下,随着小波分解层数的增加,压缩比增大,而峰值信噪比随之下降;而在相同小波分解层数下,随着扫描次数的增加,峰值信噪比显著提升,而压缩比明显下降。