Compression using Wavelet Transform

Audio compression has become one of the basic technologies of the multimedia age. The change in the telecommunication infrastructure, in recent years, from circuit switched to packet switched systems has also reflected on the way that speech and audio signals are carried in present systems. In many applications, such as the design of multimedia workstations and high quality audio transmission and storage, the goal is to achieve transparent coding of audio and speech signals at the lowest possible data rates. In other words, bandwidth cost money, therefore, the transmission and storage of information becomes costly. However, if we can use less data, both transmission and storage become cheaper. Further reduction in bit rate is an attractive proposition in applications like remote broadcast lines, studio links, satellite transmission of high quality audio and voice over internet

Adaptive Variable Degree-k Zero-Trees for Re-Encoding of Perceptually Quantized Wavelet-Packet Transformed Audio and High Quality Speech

A fast, efficient and scalable algorithm is proposed, in this paper, for re-encoding of perceptually quantized wavelet-packet transform (WPT) coefficients of audio and high quality speech and is called "adaptive variable degree-k zero-trees" (AVDZ). The quantization process is carried out by taking into account some basic perceptual considerations, and achieves good subjective quality with low complexity. The performance of the proposed AVDZ algorithm is compared with two other zero-tree-based schemes comprising: 1- Embedded Zero-tree Wavelet (EZW) and 2- The set partitioning in hierarchical trees (SPIHT). Since EZW and SPIHT are designed for image compression, some modifications are incorporated in these schemes for their better matching to audio signals. It is shown that the proposed modifications can improve their performance by about 15-25%. Furthermore, it is concluded that the proposed AVDZ algorithm outperforms these modified versions in terms of both output average bit-rates and computation times.Comment: 30 pages (Double space), 15 figures, 5 tables, ISRN Signal Processing (in Press

Traditional Psychoacoustic Model and Daubechies Wavelets for Enhanced Speech Coder Performance

Speech compression techniques based on traditional psychoacoustic model have been proposed by many researchers. We have suggested Discrete Wavelet Transform (DWT) supported by the same psychoacoustic model for speech compression. This paper presents a traditional psychoacoustic model to process equal partitions of total bandwidth spectrum of audio signal frequency to reduce redundancy by filtering out the tones and noise masker in speech signal. Here, the uniform filter banks are used for efficient computations and selection of appropriate threshold level for better compression of Discrete Wavelet Transformed coefficients. Daubechies wavelet filter bank is a nonlinear and asymmetric wavelet filter bank. It is equivalent to cochlear filter of human hearing system. The resemblance between Daubechies Filter Bank and our hearing system is used to develop the novel speech coder. Results have shown better performance in terms of compression factor (CF) and Signal-to-Noise Ratio (SNR) as compare to the methods suggested earlier

Audio encoding based on the empirical mode decomposition

National audienceThis paper deals with a new approach for perceptual audio encoding, based on the Empirical Mode Decomposition (EMD). The audio signal is decomposed adaptively into intrinsic oscillatory components by EMD called Intrinsic Mode Functions (IMFs), which can be fully described by their extrema. These extrema are encoded after an appropriate thresholding scheme controlled by a psycho-acoustic model. The decoder recovers the original signal after IMFs reconstruction by means of spline interpolation and their summation. The proposed approach is applied to different audio signals and results are compared to wavelets and to MPEG1-layer3 (MP3)approaches. Relying on exhaustive simulations, the obtained results show that the proposed compression scheme performs better than the MP3 and the wavelet approach in terms of bit rate and audio quality

Wavelet Filter Banks in Perceptual Audio Coding

This thesis studies the application of the wavelet filter bank (WFB) in perceptual audio coding by providing brief overviews of perceptual coding, psychoacoustics, wavelet theory, and existing wavelet coding algorithms. Furthermore, it describes the poor frequency localization property of the WFB and explores one filter design method, in particular, for improving channel separation between the wavelet bands. A wavelet audio coder has also been developed by the author to test the new filters. Preliminary tests indicate that the new filters provide some improvement over other wavelet filters when coding audio signals that are stationary-like and contain only a few harmonic components, and similar results for other types of audio signals that contain many spectral and temporal components. It has been found that the WFB provides a flexible decomposition scheme through the choice of the tree structure and basis filter, but at the cost of poor localization properties. This flexibility can be a benefit in the context of audio coding but the poor localization properties represent a drawback. Determining ways to fully utilize this flexibility, while minimizing the effects of poor time-frequency localization, is an area that is still very much open for research

Audio Compression using a Modified Vector Quantization algorithm for Mastering Applications

Audio data compression is used to reduce the transmission bandwidth and storage requirements of audio data. It is the second stage in the audio mastering process with audio equalization being the first stage. Compression algorithms such as BSAC, MP3 and AAC are used as standards in this paper. The challenge faced in audio compression is compressing the signal at low bit rates. The previous algorithms which work well at low bit rates cannot be dominant at higher bit rates and vice-versa. This paper proposes an altered form of vector quantization algorithm which produces a scalable bit stream which has a number of fine layers of audio fidelity. This modified form of the vector quantization algorithm is used to generate a perceptually audio coder which is scalable and uses the quantization and encoding stages which are responsible for the psychoacoustic and arithmetical terminations that are actually detached as practically all the data detached during the prediction phases at the encoder side is supplemented towards the audio signal at decoder stage. Therefore, clearly the quantization phase which is modified to produce a bit stream which is scalable. This modified algorithm works well at both lower and higher bit rates. Subjective evaluations were done by audio professionals using the MUSHRA test and the mean normalized scores at various bit rates was noted and compared with the previous algorithms

Audio encoding using Huang and Hilbert transforms

International audienceIn this paper an audio coding scheme based on the Empirical Mode Decomposition (EMD) in association with the Hilbert transform is presented. The audio signal is decomposed adaptively into intrinsic oscillatory components called Intrinsic Mode Functions (IMFs) by EMD, and the associated instantaneous amplitudes and the instantaneous phases are calculated. The basic principle of the proposed approach consists in encoding the instantaneous amplitudes by linear prediction and the instantaneous phases by scalar quantization. The decoder recovers the original signal from IMFs reconstruction by demodulation and summation. The compression method is applied to different audio signals, and results are compared to MP3 a variable bit rate coder and to wavelet approaches

Scalable and perceptual audio compression

This thesis deals with scalable perceptual audio compression. Two scalable perceptual solutions as well as a scalable to lossless solution are proposed and investigated. One of the scalable perceptual solutions is built around sinusoidal modelling of the audio signal whilst the other is built on a transform coding paradigm. The scalable coders are shown to scale both in a waveform matching manner as well as a psychoacoustic manner. In order to measure the psychoacoustic scalability of the systems investigated in this thesis, the similarity between the original signal\u27s psychoacoustic parameters and that of the synthesized signal are compared. The psychoacoustic parameters used are loudness, sharpness, tonahty and roughness. This analysis technique is a novel method used in this thesis and it allows an insight into the perceptual distortion that has been introduced by any coder analyzed in this manner

Масштабируемые аудиоречевые кодеры на основе адаптивного частотно-временного анализа звуковых сигналов

In the paper is discussed the methods of perceptual sub-band audio signal processing with the dynamic time-frequency map transformation based on the discrete wavelet packet (WP) transform. The advantages of it is that the growing process of WP tree is going from the top to down without returning to smaller scale levels of decomposition and needing to build a complete WP tree, that corresponds to the concept of scalable audio/speech coders implementation in real time. The objective quality assessment of proposed coders based techniques PEMO-Q and comparing with the widespread encoders Opus and Vorbis are given. It shows that the reconstructed signal complies with ITU-R PEAQ at a high compression ratio up to 18 times or more, does not contain artifacts and noise to mask ration less -9 dB.В статье рассматриваются методы перцептуальной субполосной обработки звуковых сигналов с динамической трансформацией частотно-временного плана на основе пакетного дискретного вейвлет-преобразования (ПДВП), достоинством которых является то, что рост дерева осуществляется сверху вниз, без возвратов на меньшие масштабные уровни преобразования и необходимости построения полного дерева ПДВП, что соответствует концепции реализации масштабируемых аудиоречевых кодеров в реальном масштабе времени. Приводятся объективные оценки качества предлагаемых кодеров на основе методики PEMO-Q и сравнения с широко распространенными кодерами Opus и Vorbis, которые показывают, что реконструированный сигнал соответствует требованиям стандарта ITU-R PEAQ при высокой степени компрессии в 18 и более раз, не содержит артефактов: отношение мощности шума к порогу маскирования 〖NMR〗_total меньше –9 дБ