Dynamic selective information hiding based on search order coding with low bit rate

Abstract

A low bit rate information hiding scheme is important for efficient communication. According to our observation, in a search order coding based (SOC based) hiding method, the case distribution generated from different images and from different secret strings is different. Based on this characteristic, we designed a dynamic selective, SOC based, information hiding scheme to achieve a desirable compression effect. That is, depending on different case distributions, we used different coding modes to reduce the bit rate more effectively. The main concept of our design is to let the two cases that occur most frequently use one-bit indicators and to let the remaining two cases use four-bit indicators to indicate the following coding types. The experimental results showed that the proposed scheme has a lower bit rate than other SOC based information hiding schemes. As a result, the proposed information hiding scheme is more practical for real world applications.     

语音编码抗信道误码保护算法

为了提高在高误码率窄带无线信道下的合成语音质量,提出了一种信源信道联合编解码保护的语音编码抗误码算法。该算法在编码端利用编码后的冗余度进行BCH编码和奇偶校验以保护对语音合成质量影响较大的参数;在解码端对清浊音参数采用分支判决和改进的最大后验概率算法进行恢复,在浊音帧对线谱对（LSP）参数进行基于信源信道联合特性的线谱对参数差错后处理,在清音帧采用BCH解码和前向替代。该算法在不消耗任何额外带宽且无算法延时的条件下可以显著提高语音编码抗信道误码能力和恶劣信道条件下的合成语音质量。仿真实验显示,在较高信道误码率下平均谱失真降低了25％～36．1％,平均意见得分（MOS）提高了12．33％。     

Bit rate reduction techniques for absolute moment block truncation coding

Abstract

Block Truncation Coding uses a two‐level moment preserving quantizer that adapts to local properties of the images. It has the features of low computation load and low memory requirement while its bit rate is only 2.0 bits per pixel. A more efficient algorithm, the absolute moment BTC (AMBTC) has been extensively used in the field of signal compression because of its simple computation and better MSE performance. We propose postprocessing methods to further reduce the entropy of two output data of AMBTC, including the bit map and two quantization data (a, b). A block of a 2×4 bit map is packaged into a byte‐oriented symbol. The entropy can be reduced from 0.965 bpp to 0.917 bpp on average for our test images. The two subimages of quantization data (a, b) are postprocessed by the Peano Scan. This postprocess can further reduce differential entropy about 0.4 bit for a 4×4 block. By applying arithmetic coding, the total bit reduction is about 0.3～0.4 bpp. The bit rate can reach 1.6～1.7 bpp with the same quality as traditional AMBTC.     

Adaptive fractal image coding in subband domain

Abstract

In this paper, we propose and evaluate a method for fractal image coding in the subband domain. The subband decomposition scheme acts as a classifier, which can efficiently reduce encoding time. The proposed fractal image coding scheme is an adaptive one. The adaptability is based on the variance of each subband. At each subband, the scheme adaptively sets the map block size that should be encoded. In addition, the domain blocks are adaptively restricted to the neighborhood of their respective range block. Simulation results show that good picture quality of the coded image is obtained at 0.370 bpp. It also indicates that such an adaptive scheme makes a better trade‐off between the required bit rate and picture quality than a fixed size one. Moreover, the adaptive shceme can save a large amount of time.     

Colour image coding scheme using absolute moment block truncation coding and block prediction technique

Abstract

A predictive colour image compression scheme based on absolute moment block truncation coding is proposed. In this scheme, the high correlations among neighbouring image blocks are exploited by using the similar block prediction technique. In addition, the bit plane omission technique and the coding of quantisation levels are used to cut down the storage cost of smooth blocks and complex blocks respectively. According to the experimental results, the proposed scheme provides better performance than the comparative schemes based on block truncation coding. It provides better image qualities of compressed images at low bit rates. Meanwhile, it consumes very little computational cost. In other words, the proposed scheme is quite suitable for real time multimedia applications.     

Intra mode decision and frame layer Lagrange multiplier adjustment scheme for H.264 based on structural similarity

H.264 takes rate distortion optimisation (RDO) technique to perform intra and inter mode decision and achieves higher coding efficiency, but the objective distortion metric such as mean square error (MSE) is employed in traditional RDO framework, which cannot acquire optimal subjective quality. In this paper, structural similarity (SSIM)-based subjective distortion is applied to RDO-based intra mode decision in H.264 I frame video coding, and a linear SSIM distortion model is firstly proposed and SSIM-based rate distortion cost function for intra mode decision is defined. Furthermore, a content adaptive frame layer Lagrange multiplier adjustment scheme is proposed to balance the tradeoff between rate and SSIM distortion better. Experimental results show that, the proposed method encodes image structural information more effectively and thus acquires better perceptual quality and subjective RDO performance compared with objective distortion-based RDO method. Under the same perceptual quality, our scheme achieves about 8·03% I frame bit rate reduction on average for various sequences over MSE-based RDO employed in JM reference software.     

Iterative optimization for joint design of source and channel codes using genetic algorithms

Abstract

This paper presents a novel algorithm for the joint design of source and channel codes. In the algorithm, channel‐optimized vector quantization (COVQ) and rate‐punctured convolutional coding (RCPC) are used for design of the source code and the channel code, respectively. We employ the genetic algorithm (GA) to prevent the design of COVQ from falling into a poor local optimum. We also adopt the GA to reduce the computational time needed for realizing the unequal error protection scheme best matched to the COVQ. Both the GA‐based source coding and channel coding scheme are then iteratively combined to achieve a near global optimal solution for the joint design. Numerical results show that the algorithm can be an effective alternative for applications where high rate‐distortion performance and low computational complexity are desired.     

一种新的汉语连续语音声调评测算法

提出一种新的连续语音的声调评测算法,该算法可应用于计算机辅助语言学习系统和普通话水平测试中的声调评测。考虑到连续语音声调受上下文之间的相互影响,采用三音节单元建立高斯混合模型(Gaussian Mixture Model, GMM),三音节中辅音部分用Spline插值法拟合声调曲线来反映音节间基音频率的转移信息,并利用Fujisaki模型去除语句的语调和说话人个性特征,只对基频曲线中的声调特征建模。实验结果显示,相比于传统方法,采用三音节Spline插值和Fujisaki改进特征的方法使得机器与人工打分的相似度在测试集中分别提高了8.75%和14.09%。     

超低速率MELP语音编码算法研究

在语音编码算法中,混和激励线性预测(MELP)算法因为能更好的模拟自然语言特征,在低速率上能合成较高质量的语音,而成为现代低速率语音编码中最有潜力的算法之一。但在无线通信、卫星通信以及军用和保密通信中,信道带宽成为一个突出的问题,因此对更低速率语音压缩编码技术乃至超低速率的语音压缩编码技术的研究是非常有必要的。针对语音通信中关于极低速率的要求,深入分析了现今的几种基于MELP的低速率语音编码算法,对其原理以及关键技术进行了归纳总结,并对语音质量进行了比较。     

修正倒谱和动态规划的基频估计算法

基音频率是语音信号处理中的一个重要参数。倍频、半频错误以及清浊音判决的可靠性等问题一直是基频估计中的难点问题。在对语音信号的倒谱进行适当修正的基础上,提出了一种高精度的基频估计算法。该算法根据倒谱、短时能量和短时过零率在清音段和浊音段的不同表现,构造了一个清浊音判决函数,大大提高了清浊音判决精度;然后利用动态规划技术进行基频跟踪。在构造代价函数时．充分考虑了基频连续性的影响,从而使该算法既能有效地避免倍频和半频错误,又能体现出基频的自然加倍和减半。通过与现有的几种效果较好的方法进行对比实验,结果表明该算法具有准确率高、基频轨迹平滑的优点,利用该算法得到的基频轨迹基本不需要进行后期平滑处理。     

Progressive image transmission using a prefilter and a modified difference pyramid structure

Abstract

Pyramid data structures have played an important role in progressive image transmission. Over the years, the reduced difference pyramid (RDP) has been found to be one of the best data structure. The RDP takes the differences between the neighboring nodes at the same level. The new modified difference pyramid (MDP) data structure, developed in this paper, takes the differences between successive levels. Simulation results show that both the bit rate and the complexity of the receiver for the MDP structure are lower than those for the RDP structure at the same quality.

An MDP coding process which incorporates a prefilter is also proposed in this paper. Simulation results show it can provide good quality (in a subjective sense) reconstructed images at a lower bit rate than the unfiltered scheme can. Also, acceptable intermediate images are interpolated via the repetition method and via the cubic convolution method to get images which are the same size as the original. Results are compared.     

Evaluation and Compensation of Quantization Effect on Servo Performance for Hard Disk Drives

We investigated the quantization effect on the servo performance of a 1.8-in hard disk drive by changing the bits of the proposed quantizer model. We measured and analyzed the frequency response of the quantizer with different bits. The corresponding error rejection functions show that the poor rejection ability of the servo loop to low-frequency disturbances is caused by the quantizer in addition to the actuator pivot friction behavior. We propose a simple and low-cost scaling scheme to compensate the effect of the quantizer. With the compensation, the effect on the rejection ability is mostly due to the friction. Therefore, the effects from quantization and friction on the error rejection function can be differentiated, and the quantization and friction induced problems can be dealt with separately in the servo loop. In addition, through the proposed quantization model and measurement methodology, suitable bit resolution for the quantizer with and without the compensation can be identified.     

A simplified SPIHT algorithm

Abstract

Based on the SPIHT algorithms, we define two modifications to develop a simpler image coding method. The first concept is obtained from the relationship between the bit‐planes and the target bit‐rate. The second concept is obtained from the relationship between the initial threshold and the target bit‐rate. Based on the abovementioned concepts, we can discard the refinement pass and improve the image quality at different target bit‐rates. The simulation results show that in comparison with the original SPIHT algorithm, the proposed algorithm can reduce memory usage by approximately 50% and computation time by approximately 30% with an acceptable PSNR loss.     

Glottal closure instant and voice source analysis using time-scale lines of maximum amplitude

¹Time-scale representation of voiced speech is applied to voice quality analysis, by introducing the Line of Maximum Amplitude (LoMA) method. This representation takes advantage of the tree patterns observed for voiced speech periods in the time-scale domain. For each period, the optimal LoMA is computed by linking amplitude maxima at each scale of a wavelet transform, using a dynamic programming algorithm. A time-scale analysis of the linear acoustic model of speech production shows several interesting properties. The LoMA points to the glottal closure instants. The LoMA phase delay is linked to the voice open quotient. The cumulated amplitude along the LoMA is related to voicing amplitude. The LoMA spectral centre of gravity is an indication of voice spectral tilt. Following these theoretical considerations, experimental results are reported. Comparative evaluation demonstrates that the LoMA is an effective method for the detection of Glottal Closure Instants (GCI). The effectiveness of LoMA analysis for open quotient, amplitude and spectral tilt estimations is also discussed with the help of some examples.     

Optimization of wireframe model adaptation and motion estimation in a rate-distortion framework

A rate-distortion framework is used to define a very low-bit-rate coding scheme based on wireframe model adaptation and optimized selection of motion estimators. This technique achieves maximum reconstructed image quality under the constraint of a target bit rate for the coding of the vector field and the wireframe representation information. First, a complete scheme is proposed for hybrid two-dimensional (2D) and 3D motion estimation and compensation. The wireframe adaptation and updating is optimized for hybrid motion estimation in the rate distortion sense. A more sophisticated technique, adapted to the requirements of a very low-bit-rate coder is also proposed which considers also the transmission of the prediction error corresponding to the particular choice of the motion estimator for each object in the scene. Experimental results illustrating the performance of the proposed techniques in very low-bit-rate image sequence coding application areas are presented and evaluated. © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 238–247, 1998     

An improved construction of block‐coded modulation

Abstract

The traditional block‐coded modulation scheme is based on set partitioning of a two‐dimensional signal constellation. In this paper, we propose an improved design of the block‐coded modulation scheme which is based on set partitioning of a block modulation code at some coding levels. With no inferior error performance, the proposed scheme is far superior as regards its reduced decoding complexity.     

The hardware design of a speaker‐independent speech recognizer

Abstract

This paper presents a hardware approach to the realization of a speaker‐independent speech recognizer. This hardware includes a feature normalizer, a vector quantizer, and a hidden Markov model (HMM) scoring processor. It can meet real time requirements in moderate vocabulary applications. The finite‐register‐length effect is investigated so that the register length for representing the model parameters and the computation results can be determined. An error analysis for the HMM scoring procedure is also derived.     

Efficient bit‐plane coding scheme for fine granular scalable video coding

In this paper, we propose a new efficient bit‐plane coding method for fine granular scalable (FGS) video coding. The general structure of the proposed bit‐plane coding method is based on the traditional bit‐plane coding scheme in MPEG‐4 FGS. However, to enhance coding efficiency of bit‐plane encoding, we apply an efficient probability estimation scheme through employing the binary arithmetic coding. For probability estimation, various context models are designed to take advantage of the characteristics of each bit‐plane as well as the correlations of symbols among different bit‐planes. Experimental results show that the proposed FGS coding scheme provides better coding performance, compared to the well‐known FGS coding schemes in MPEG‐4 FGS and JSVM. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 113–120, 2006.     

语音编码算法的神经网络增益滤波器

增益-波形乘积码书结构广泛用于 CELP 语音编码算法, 它们使用 Levinson-Durbin(L-D)方法更新增益滤波器系数. 本文对 BP 神经网络算法与 L-D 方法进行了比较. 用 BP 神经网络增益滤波器进行语音编码, 其计算量仅为 G.728 的 L-D 方法的 6.7%, 但平均分段 SNR 高出 G.728 算法 0.156 dB. 同时, 用 BP 神经网络算法评价了 16 和 20 样点激励矢量增益滤波器, 效果同样很好. 但是, 由于考察增益预测器时量化器还不存在, 因此无法用量化信噪比评价滤波器性能. 本文提出一种信噪比估计方法, 可使增益预测器的优化与量化问题分开处理. 实验表明用这种信噪比估计方法选择增益滤波器十分有效.     

基于注意力机制的LSTM语音情感主要特征选择

传统的语音情感识别方式采用的语音特征具有数据量大且无关特征多的特点,因此选择出与情感相关的语音特征具有重要意义。通过提出将注意力机制结合长短时记忆网络(Long Short Term Memory, LSTM),根据注意力权重进行特征选择,在两个数据集上进行了实验。结果发现:(1)基于注意力机制的LSTM相比于单独的LSTM模型,识别率提高了5.4%,可见此算法有效提高了模型的识别效果;(2)注意力机制是一种有效的特征选择方法。采用注意力机制选择出了具有实际物理意义的声学特征子集,此特征集相比于原有公用特征集在降低了维数的情况下,提高了识别准确率;(3)根据选择结果对声学特征进行分析,发现有声片段长度特征、无声片段长度特征、梅尔倒谱系数(Mel-Frequency Cepstral Coefficient, MFCC)、F0基频等特征与情感识别具有较大相关性。