基于复杂性寻踪的非独立图像盲分离

复杂性寻踪是近期发展起来的一种结合非高斯性和时间相关的投影寻踪方法,目的是在多元数据中找到一个投影方向,使得数据在该方向上的投影具有最令人感兴趣的结构。它是投影寻踪方法在时间序列应用上的扩展,相似于依赖时间的信号源盲分离和独立分离分析。由相互独立的图像混合而成的混合图像的盲分离技术已经相当成熟,但对非独立混合的图像的盲分离仍然是个难题。从时间序列的复杂性寻踪出发,推导出一个复杂性寻踪的定点算法。该算法是经典的快速独立分量分析算法（FastICA）的扩展,继承了FastICA的优点,简单易行,不需要用户选择学习率,并且算法具有快速稳定收敛的性质。该算法应用到非独立图像的混合图像的盲分离时,取得了较好的分离结果。     

Complexity pursuit: separating interesting components from time series

A generalization of projection pursuit for time series, that is, signals with time structure, is introduced. The goal is to find projections of time series that have interesting structure, defined using criteria related to Kolmogoroff complexity or coding length. Interesting signals are those that can be coded with a short code length. We derive a simple approximation of coding length that takes into account both the nongaussianity and the autocorrelations of the time series. Also, we derive a simple algorithm for its approximative optimization. The resulting method is closely related to blind separation of nongaussian, time-dependent source signals.     

The Fixed-Point Algorithm and Maximum Likelihood Estimation for Independent Component Analysis

The author previously introduced a fast fixed-point algorithm for independent component analysis. The algorithm was derived from objective functions motivated by projection pursuit. In this paper, it is shown that the algorithm is closely connected to maximum likelihood estimation as well. The basic fixed-point algorithm maximizes the likelihood under the constraint of decorrelation, if the score function is used as the nonlinearity. Modifications of the algorithm maximize the likelihood without constraints.     

Real-time DSP implementation of motion-JPEG2000 using overlapped block transferring and parallel-pass methods

This paper presents a real-time implementation of Motion-JPEG2000 encoder using a fixed-point DSP chip. Among several modules in JPEG2000 encoder, the lifting algorithm for discrete wavelet transform (DWT) and the embedded block coding with optimized truncation (EBCOT) comprise more than 85% of the encoding complexity. Thus, it is very important to design and optimize these two modules in order to increase the performance of the hardware implementation. First we propose an overlapped block transferring (OBT) method that can significantly improve the performance of the lifting algorithm for DWT by increasing the cache hit rate. We show that the execution time of the lifting scheme can be further reduced by programming the DSP software using the single instruction multiple data (SIMD) instructions and the super scalar pipeline structure. Moreover, we introduce a parallel-pass method for fast implementation of EBCOT. This method reduces the processing time of EBCOT by processing the three coding passes of the same bit-plane in parallel. Experimental results show that our developed Motion-JPEG2000 DSP system meets the common requirement of the real-time video coding [30 frames/s (fps)] and is proven to be a practical and efficient DSP solution.     

TD-LTE系统中秩指示的编码及DSP实现

秩指示RI是3GPP LTE系统中一种重要的MIMO反馈信息.3GPP协议给出了RI的编码方法,是一种简单的线性分组码.采用TI TMS320C6455定点DSP,编程实现协议规定的编码,方法为循环查表法,采用的编程语言为汇编,仿真平台为CCS3.3.该方案算法简单、耗时少,已应用于TD-LTE无线综合测试仪表的开发中...     

一种用于海量图像多分辨率局部重建的压缩算法

论文通过对Shaprio嵌入式小波系数零树编码方法的误差进行分析,针对海量图像数据量庞大的特点,提出了一种便于海量图像局部重建的量化算法。在该算法的基础上,结合位平面编码和游程编码,得到了比较高的压缩比。实验证明这种方法简单有效,易于编程实现,在对相关项目所涉及的海量图像进行处理过程中取得了很好的效果,是一种行之有效的压缩方法。     

改进ICA算法及其在作物光谱分类中的应用

针对传统的固定点算法对分离矩阵初始值敏感的问题,提出一种改进的独立分量分析(ICA)算法,通过在传统的算法核心迭代过程中加入搜索因子,降低算法对矩阵初始值的依赖,提高处理效率。将ICA算法应用于作物精细光谱的分类,分别利用传统固定点算法和改进的固定点算法对混合光谱进行信息提取与分离。实验证明,改进的ICA算法在与传统算法作物光谱分类效果相当的情况下,迭代次数减少26%,提高了独立分量的分离效率,是一种有效的作物光谱分类方法。     

一种基于定点DSP的YCbCr到HSV的快速转换算法*

通过分析YCbCr到RGB以及RGB到HSV之间转换的算法,提出一种YCbCr空间转换到HSV空间的快速算法。在该算法中分别使用了移位运算和查表法代替了浮点乘法运算,从而显著提高了算法在DSP上的运行速度。另外,转换时Y分量不再参与计算,从而进一步降低了运算复杂度。最后实验证明,在DSP平台上,该算法比传统算法能节省80%的计算时间,在PC平台上能节省46%的计算时间。因此,提出的算法在车牌识别、火焰检测等实时视频分析应用中有广泛的应用性。     

Gaussian sum approximation for non-linear fixed-point prediction

Fixed-point prediction is the estimation of the state of a system at a future fixed time based on a noisy measurement with sequence length that increases with current time. A recursive algorithm for generating fixed-point prediction is given using the integrated form of the chain rule. For non-linear systems no general filter solution exists ; thus a gaussian sum approximation is developed. The method provides a numerical approximation for the time-dependant a posteriori density from which a filter can be generated.     

低冗余二维码汉字编码研究

随着二维码应用领域的不断扩大,二维码的优化和改进也势在必行。二维码在汉字编码过程中采用定长编码模式,忽略了汉字使用频率对二维码汉字编码效率的影响,存在着较大的编码冗余。采用变长编码算法可以减少高频汉字的编码长度,降低二维码汉字编码的平均编码长度,增加编码容量。首先,结合常用汉字的使用频率,对二维码的汉字编码进行分段处理,分析并制定基于汉字使用频率的变长汉字编码表;其次,在不破坏二维码原有编码结构的情况下,仅对二维码的汉字编码采用变长编码方式;最后,分析并比较二维码定长汉字编码算法和二维码变长编码算法的时间性能和空间性能,给出优化及改进思路。实验证明,二维码变长编码算法可降低二维码汉字编码18.4%的冗余。     

基于平均偏差排序的快速分形图像编码

分形图像编码是一种很有前途的压缩技术，但由于其编码时间长、计算复杂性高，因而阻碍了它的广泛应用，针对此问题，提出了一种快速的分形编码算法。这种算法是首先将码本按照平均偏差大小进行排序，然后使用二分搜索法寻找给定Range块在平均偏差意义下的最好匹配码块，进而利用一个联系均方根和平均偏差的不等式来在这个最好匹配码块的邻域中搜索Range块在均方根意义下的最佳匹配码块。实验结果显示，在主观质量略有下降的条件下，该算法编码过程显著快于基本分形算法。     

基于字符频率的快速通用数据压缩算法

本文描述了一种简单快速的通用数据压缩算法，这是一种自适应的变长编码算法，为获得更好的压缩效率，在该算法中同时集成了游程长度编码技术。     

基于二次筛选的回溯广义正交匹配追踪算法的稀疏信号重构

压缩感知是一种新型的信号采样及重构理论,高效的信号重构算法是压缩感知由理论转向实际应用的枢纽。为了更精确地重构出原始稀疏信号,本文提出一种基于二次筛选的回溯广义正交匹配追踪算法。首先采用内积匹配准则选出较大数目的相关原子,提高原子的利用率。其次利用广义Jaccard系数准则对已选出的原子进行二次筛选,得到最匹配的原子,优化原子选取方式。实验结果表明,在不同稀疏度和观测值下进行信号重构,相比于回溯广义正交匹配追踪算法、正交匹配追踪算法及子空间追踪算法,本文算法在重构误差及重构成功率方面有较大的优越性。     

Fixed point implementation of fast Kalman predictors

In this note we study scaling rules and roundoff noise variances in a fixed-point implementation of the Kalman predictor for an ARMA time series observed noise free. The Kalman predictor is realized in a fast form that uses the so-called fast Kalman gain algorithm. The algorithm for the gain is fixed point. Scaling rules and expressions for rounding error variances are derived. The numerical results show that the fixed-point realization performs very close to the floating point realization for relatively low-order ARMA time series that are not too narrow band. The predictor has been implemented in 16-bit fixed-point arithmetic on an INTEL 8086 microprocessor, and in 16-bit floating-point arithmetic on an INTEL 8080. Fixed-point code was written in Assembly language and floating-point code was written in Fortran. Experimental results were obtained by running the fixed- and floating-point filters on identical data sets. All experiments were carried out on an INTEL MIDS 230 development system.     

基于CMP算法的正弦波模型研究

BP3,AAC等高质量音频编码方法已经成为国际标准,目前研究的热点已转向高效率更低比特率的编码算法。正弦波模型作为其中的一种解决方法,正引起越来越多的重视。本文提出一种新的CMP（Consistent matching pursuit)算法来处理正弦波模型。它在分析时将合成过程颠簸在内,保证了分析与合成时的一致性;同时又利用了MP算法固有的高度冗余性;而且还采取了一些措施有效地降低了的分析过程的计算量。因而和经典的迭代法相比,可以以减少的计算量获得更好的性能。而且它还非常适合于作压缩域的各种处理。     

Generating and coding of fractal graphs by neural network andmathematical morphology methods

We present an algorithm for generating a class of self-similar (fractal) graphs using simple probabilistic logic neuron networks and show that the graphs can be represented by a set of compressed encoding. An algorithm for quickly finding the coding, i.e., recognizing the corresponding graphs, is given and the coding are shown to be optimal (i.e., of minimal length). The same graphs can also be generated by a mathematical morphology method. These results may possibly have applications in image compression and pattern recognition.     

K-means聚类方法下的复数图像群组稀疏编码降噪算法

稀疏编码已经广泛应用于复数图像的降噪问题,其中,近些年提出的分组稀疏编码由于能够充分利用同一分组图像块的相似性,在滤除噪声和提高降噪信噪比方面具有更大的优势.研究了一种基于K-means聚类方法的复数图像分组稀疏降噪算法,通过改进聚类算法,验证了K-means算法对分组稀疏编码算法的分组有效性.采用在线复数词典训练算法快速获取编码字典,并运用分组正交匹配追踪算法,实现了分组图像块的稀疏编码.通过限制每一分组图像块中编码的相似性,有效抑制了对图像块中噪声的编码,提高了对复数图像的降噪效果.为验证算法的有效性,对模拟和真实的干涉合成孔径雷达图像的仿真噪声进行了定量分析,证明了所提算法相对于以前的分组稀疏编码算法在峰值信噪比指标上有一定的提升.最后对真实的干涉合成孔径雷达图像进行了降噪,进一步验证了所提降噪算法对于真实噪声的降噪能力.     

Analyzing very large time series using suffix arrays

Suffix arrays form a powerful data structure for pattern detection and matching. In a previous work, we presented a novel algorithm (COV) which is the only algorithm that allows the detection of all repeated patterns in a time series by using the actual suffix array. However, the requirements for storing the actual suffix strings even on external media makes the use of suffix arrays impossible for very large time series. We have already proved that using the concept of Longest Expected Repeated Pattern (LERP) allows the actual suffices to be stored in linear capacity O(n) on external media. The repeated pattern detection using LERP has analogous time complexity, and thus makes the analysis of large time series feasible and limited only to the size of the external media and not memory. Yet, there are cases when hardware limitations might be an obstacle for the analysis of very larger time series of size comparable to hard disk capacity. With the Moving LERP (MLERP) method introduced in this paper, it is possible to analyze very large time series (of size tens or hundreds thousands times larger than what the LERP can analyze) by maximal utilization of the available hardware. Further, when empirical knowledge related to the distribution of repeated pattern’s length is available, the proposed method (MLERP) can achieve better time performance compared to the standard LERP method and definitely much better than using any other pattern matching algorithm and applying brute force techniques which are unfeasible in logical (human) time frame. Thus, we may argue that MLERP is a very useful tool for detecting all repeated patterns in a time series regardless of its size and hardware limitations.     

Fast and robust fixed-point algorithms for independent componentanalysis

Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. We use a combination of two different approaches for linear ICA: Comon's information theoretic approach and the projection pursuit approach. Using maximum entropy approximations of differential entropy, we introduce a family of new contrast functions for ICA. These contrast functions enable both the estimation of the whole decomposition by minimizing mutual information, and estimation of individual independent components as projection pursuit directions. The statistical properties of the estimators based on such contrast functions are analyzed under the assumption of the linear mixture model, and it is shown how to choose contrast functions that are robust and/or of minimum variance. Finally, we introduce simple fixed-point algorithms for practical optimization of the contrast functions     

AVS-P10音频解码器算法分析与定点化

AVS-P10是我国第一部应用于移动环境的音频编解码国家标准。在分析AVS-P10解码算法的基础上,对参考代码进行了精简和封装。针对定点处理器应用需求,对精简后的代码进行了定点化实现和优化。分别采用CMOS评分与SNR指标,对定点解码器的解码质量进行了主、客观测试,并对优化前后的定点解码器的运算效率进行了比对测试。结果表明,提出的AVS-P10定点解码器的解码音质达到与浮点解码信号的音质相当,且运算复杂度明显下降。