Two-stage bit allocation algorithm for stereo audio coder

A new bit allocation algorithm is proposed and applied in a stereo transform coder. This algorithm is a two-stage approach based on the minimisation of perceptual distortion measured by artificial ears. At the first stage, the use of minimum frequency-weighted reconstruction error is exploited, in which the weighting factors are related to the masking threshold and the absolute hearing threshold. The bit assignment obtained at the first stage is fine tuned by a greedy algorithm of perceptual distortion versus bit rate at the second stage. A joint stereo perceptual transform coder is implemented and incorporated with this two-stage bit allocation algorithm. The listening tests show that this coder performs better than MPEG layer 2 at bit rates below 128 kbps and has the comparative quality of MPEC layer 2 at higher bit rates     

Efficient bit allocation algorithm for ISO/MPEG audio encoder

An efficient bit allocation algorithm for the ISO/MPEG audio layer 2 encoder is proposed. The resulting encoder is able to produce an ISO/MPEG compliant bit stream which is almost identical to the bit stream produced by the reference ISO/MPEG encoder suggested in IS 11172-3. More importantly, the number of computational steps is greatly reduced as compared to the method recommended by the ISO/MPEG Committee because the efficient bit allocation algorithm significantly reduces the number of iterations required. It was found that the efficient bit allocation algorithm works best when the bit rate demanded by the psychoacoustic model in order to keep the quantisation noise below the masking threshold is almost equal to the operational bit rate     

Improving the performance of MPEG audio coder layer I usingadaptive representation of bit allocation information

In general, all the spectral components of an audio signal are not preceptually significant and so the bit allocation information from the MPEG audio coder layer I often contains a sequence of zeros for all subbands at a higher frequency than a particular subband. Motivated by this, an efficient representation of the bit allocation information and its associated bit allocation algorithm is presented. Computer simulation shows that the modified version of the MPEG audio coder layer I, employing the proposed representation format, performs better in terms of sound quality than the original one     

A 128 Kb/s Hi-Fi audio codec based on adaptive transform codingwith adaptive block size MDCT

A Hi-Fi audio codec with an improved adaptive transform coding (ATC) algorithm is presented using digital signal processors (DSPs). An audio signal with a 20 kHz bandwidth sampled at 48 kHz is coded at a rate of 128 kb/s. The algorithm utilizes adaptive block size selection, which is effective for preecho suppression. A modified discrete cosine transform (MDCT) with a simple window set is employed to reduce block boundary noise without decreasing the performance of transform coding. In addition, a fast MDCT calculation algorithm, based on a fast Fourier transform, is adopted. Weighted bit allocation is employed to quantize the transformed coefficients. The codec was realized by a multiprocessor system composed of newly developed DSP boards. Subjective tests with the codec show that the coding quality is comparable to that of compact disc signals     

Low delay coder (< 25 ms) of wideband audio (20 Hz-15 kHz) scalable from 64 to 32 kbit/s

A low delay coder for speech and music signals sampled at 32kHz is described. Its algorithmic delay does not exceed 25 ms which enables audioconferencing applications without echo cancellation. Its bit rate is scalable between 64 and 32 kbit/s by steps of 8 kbit/s. The transmitter issues the binary code at 64 kbit/s with lower bit rate codes embedded in it. The receiver may operate at lower bit rates with gradual loss of quality. The proposed coder is based on a mixed scheme : the adopted solution contains elements from the CELP speech coder and frequency domain music coders. The perceptual signal is obtained in the time domain, then transformed to the frequency domain where bit allocation is calculated and transform coefficients are quantized. A first solution based on the dft is discussed, then a second solution based on a mdct with small overlap is applied. The quantization of these coefficients is done in the following way. First, a prediction of the whole spectrum is applied. Then, a mean- removed gain- shape split vq is used for amplitude spectrum quantization and a hierarchical 2- dimensional vq is used for phase spectrum quantization with amplitude correction. At the phase quantization stage, each codeword describing the selected vector index is split into parts corresponding to different bit rates. Due to the hierarchical codebook structure, truncated indices may be used, without much affecting the signal quality. Simulation results are presented and the robustness of the proposed coder is examined.     

一种频率域的盲源分离算法

提出了一种频率域基于第二特征函数的窄带信号盲分离算法，理论上证明了本方法能够从有噪观察数据中得到无噪混合矩阵估计。仿真结果表明本方法信号分离性能优于时域方法。在高信噪比时，本方法的分离信号绝对误差和比时域方法低9．5dB。     

一种基于正弦模型的音频压缩算法

提出一种适用于无线移动通信的低码率音频压缩算法。该算法基于正弦模型，而且针对极低码率的应用做了修正，提高了重建音频的质量。这些修正包括：自适应变换的分析长度，用于匹配跟踪算法和参数量化的心理声学模型以及频域的无相位音频重建算法。主观测试表明，在0.5bit/抽样的码率要求下，重建信号达到并超过了调幅广播的音频质量。     

Huffman code based error screening and channel code optimization for error concealment in perceptual audio coding (PAC) algorithms

The class of perceptual audio coding (PAC) algorithms yields efficient and high-quality stereo digital audio bitstreams at bit rates from 16 kb/sec to 128 kb/sec (and higher). To avoid "pops and clicks" in the decoded audio signals, channel error detection combined with source error concealment, or source error mitigation, techniques are preferred to pure channel error correction. One method of channel error detection is to use a high-rate block code, for example, a cyclic redundancy check (CRC) code. Several joint source-channel coding issues arise in this framework because PAC contains a fixed-to-variable source coding component in the form of Huffman codes, so that the output audio packets are of varying length. We explore two such issues. First, we develop methods for screening for undetected channel errors in the audio decoder by looking for inconsistencies between the number of bits decoded by the Huffman decoder and the number of bits in the packet as specified by control information in the bitstream. We evaluate this scheme by means of simulations of Bernoulli sources and real audio data encoded by PAC. Considerable reduction in undetected errors is obtained. Second, we consider several configurations for the channel error detection codes, in particular CRC codes. The preferred set of formats employs variable-block length, variable-rate outer codes matched to the individual audio packets, with one or more codewords used per audio packet. To maintain a constant bit rate into the channel, PAC and CRC encoding must be performed jointly, e.g., by incorporating the CRC into the bit allocation loop in the audio coder.     

Low bit rate transparent audio compression using adapted wavelets

Describes a novel wavelet based audio synthesis and coding method. The method uses optimal adaptive wavelet selection and wavelet coefficients quantization procedures together with a dynamic dictionary approach. The adaptive wavelet transform selection and transform coefficient bit allocation procedures are designed to take advantage of the masking effect in human hearing. They minimize the number of bits required to represent each frame of audio material at a fixed distortion level. The dynamic dictionary greatly reduces statistical redundancies in the audio source. Experiments indicate that the proposed adaptive wavelet selection procedure by itself can achieve almost transparent coding of monophonic compact disk (CD) quality signals (sampled at 44.1 kHz) at bit rates of 64-70 kilobits per second (kb/s). The combined adaptive wavelet selection and dynamic dictionary coding procedures achieve almost transparent coding of monophonic CD quality signals at bit rates of 48-66 kb/s     

High-quality audio compression using an adaptive wavelet packetdecomposition and psychoacoustic modeling

This paper presents a technique to incorporate psychoacoustic models into an adaptive wavelet packet scheme to achieve perceptually transparent compression of high-quality (34.1 kHz) audio signals at about 45 kb/s. The filter bank structure adapts according to psychoacoustic criteria and according to the computational complexity that is available at the decoder. This permits software implementations that can perform according to the computational power available in order to achieve real time coding/decoding. The bit allocation scheme is an adapted zero-tree algorithm that also takes input from the psychoacoustic model. The measure of performance is a quantity called subband perceptual rate, which the filter bank structure adapts to approach the perceptual entropy (PE) as closely as possible. In addition, this method is also amenable to progressive transmission, that is, it can achieve the best quality of reconstruction possible considering the size of the bit stream available at the encoder. The result is a variable-rate compression scheme for high-quality audio that takes into account the allowed computational complexity, the available bit-budget, and the psychoacoustic criteria for transparent coding. This paper thus provides a novel scheme to marry the results in wavelet packets and perceptual coding to construct an algorithm that is well suited to high-quality audio transfer for Internet and storage applications     

Nonlinear quantisation for pixel domain distributed video coding

A nonlinear quantisation algorithm for pixel domain distributed video codec (DVC) is proposed. A residual signal is generated at the encoder considering the Wyner-Ziv frame to be encoded and adjacent reference frames and this residual signal is quantised using a nonlinear quantiser. The proposed algorithm is simulated for a number of test video sequences and the results depict a significant improvement of rate distortion performance, by reducing the bit rate while keeping the same PSNR when compared with available pixel domain DVC codec that uses a linear quantiser.     

基于离散小波变换和复倒谱的音频水印算法

提出了一种新的基于离散小波变换和复倒谱的音频水印算法.将音频信号进行3级小波分解,在第3级上对小波系数加回声,根据不同的水印值选择不同的回声延迟,然后重构音频信号.检测时采用复倒谱变换,实现了水印的盲检测.实验表明,该算法具有很好的透明性和鲁棒性,能抵抗重采样,低通滤波等常见攻击和抖动,随机剪切等同步攻击.     

基于小波变换和音质模型的音频编码算法研究

音频编码要解决的问题是以最小感知失真用低速率表达音频信号.本文设计了一种基于正交小波变换和音质模型的自适应比特分配音频编码算法,它可以将1411.2kbit/s的双声道立体声高保真音频信号压缩成低至32kbit/s的速率,并保持很好的音频质量.     

Low bit-rate audio coder using an M-band multiresolution filterbank

A new audio coding system is proposed. Using an M-band multiresolution filter bank technique. This consists of a cascade of 4-band and 8-band filter banks. Experiments with a complete audio coding system were carried out with the proposed filter bank, masking model, bit allocation algorithm, scalar quantisation and Huffman coding. For the broadband signals tested, the proposed system resulted in near transparent quality at bit-rates of 78-91 kbit/s with low computational load. It also achieved similar performance to the MPEG layer 2 coder at 128 kbit/s     

Improving the quality of the audio sources using Gaussianity reduction technique

This research has developed a novel technique that is based on the fundamental property of background and foreground signals. Background signals are a result of the inferential summation of large number of sources, while the foreground signals are a result of limited number of sources. This makes the statistical properties of the signal very different. Using negative entropy, this article demonstrates that it is possible to obtain the foreground signals from the mixture of foreground and background signals. The technique is based on mixing the noisy recording with a similar known signal and separating the signals using negative entropy based independent component analysis (ICA). The results indicate that the technique is successful in significantly improving the quality of the audio signals.     

Subband-multipulse digital audio broadcasting for mobile receivers

The audio quality, robustness and implementational complexity of a novel mobile digital audio broadcast scheme are addressed. The audio codec proposed is based on an efficient combination of subband coding (SBC) and multipulse excited linear prediction coding (MPLPC). The bit allocation is dynamically adapted according to both the signal power in different subbands and a perceptual hearing model. Typically a segmental signal to noise ratio (SEGSNR) in excess of 30 dB associated with high fidelity subjective quality was achieved for 2.67-b/sample transmissions at a bit rate of 86 kb/s. Perceptually unimpaired audio quality was achieved for a bit error rate (BER) of about 10^-4, when injecting random errors, which was degraded for increased BERs. In order to provide robust error protection, the audio codec was also subjected to a rigorous bit sensitivity analysis. Four different forward error correction schemes were investigated in order to explore the complexity, bit rate, and robustness tradeoffs     

Efficiently self-synchronized audio watermarking for assured audio data transmission

In this paper, we propose a self-synchronization algorithm for audio watermarking to facilitate assured audio data transmission. The synchronization codes are embedded into audio with the informative data, thus the embedded data have the self-synchronization ability. To achieve robustness, we embed the synchronization codes and the hidden informative data into the low frequency coefficients in DWT (discrete wavelet transform) domain. By exploiting the time-frequency localization characteristics of DWT, the computational load in searching synchronization codes has been dramatically reduced, thus resolving the contending requirements between robustness of hidden data and efficiency of synchronization codes searching. The performance of the proposed scheme in terms of SNR (signal to noise ratio) and BER (bit error rate) is analyzed. An estimation formula that connects SNR with embedding strength has been provided to ensure the transparency of embedded data. BER under Gaussian noise corruption has been estimated to evaluate the performance of the proposed scheme. The experimental results are presented to demonstrate that the embedded data are robust against most common signal processing and attacks, such as Gaussian noise corruption, resampling, requantization, cropping, and MP3 compression.     

基于EBSBL-BO算法的L-DACS系统干扰抑制方法

L频段数字航空通信系统（L-band digital aviation communication system,L-DACS）是未来面向航路阶段的空地数据链路,其工作频段部署在两个测距仪（distance measure equipment,DME）工作频段之间,为了消除测距仪产生的高功率脉冲信号对L-DACS系统前向链路正交频分复用接收机的干扰,本文提出基于扩展稀疏贝叶斯-边界优化（extended block sparse Bayesian learning-boundary optimization,EBSBL-BO）算法的高功率DME脉冲干扰抑制方法。首先,利用L-DACS系统正交频分复用接收机的空子载波建立DME干扰信号压缩感知模型;然后,基于EBSBL-BO算法对DME信号进行重构;最后将高功率DME脉冲信号在时域消除。仿真结果显示：本文算法与其他稀疏贝叶斯重构算法相比,本文算法DME脉冲信号重构精度更高,正交频分复用接收机误码率更低,可有效改善L-DACS系统正交频分复用接收性能。     

一种基于Arnold变换的音频数字水印算法

提出了一种新的音频数字水印算法。根据音频信号时域特征分析结论确定出若干个相对稳定的特征区域,然后对每个特征区域进行DCT变换,通过对DCT系数进行比较实现了水印信息的嵌入。水印信息是二值图像,在嵌入前使用Arnold变换对图像信息进行了加密。水印的提取不需要原始音频信号的参与,而且采用并行嵌入和统计检测的方法提高了水印性能。仿真试验证明了算法的有效性和数字水印的不可感知性。     

Joint FrFT‐FFT basis compressed sensing and adaptive iterative optimization for countering suppressive jamming

Accurate suppressive jamming is a prominent problem faced by radar equipment. It is difficult to solve signal detection problems for extremely low signal to noise ratios using traditional signal processing methods. In this study, a joint sensing dictionary based compressed sensing and adaptive iterative optimization algorithm is proposed to counter suppressive jamming in information domain. Prior information of the linear frequency modulation (LFM) and suppressive jamming signals are fully used by constructing a joint sensing dictionary. The jamming sensing dictionary is further adaptively optimized to perfectly match actual jamming signals. Finally, through the precise reconstruction of the jamming signal, high detection precision of the original LFM signal is realized. The construction of sensing dictionary adopts the Pei type fast fractional Fourier decomposition method, which serves as an efficient basis for the LFM signal. The proposed adaptive iterative optimization algorithm can solve grid mismatch problems brought on by undetermined signals and quickly achieve higher detection precision. The simulation results clearly show the effectiveness of the method.