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

Steganography and steganalysis: data hiding in Vorbis audio streams

The goal of the current work is to introduce ourselves in the world of steganography and steganalysis, centering our efforts in acoustic signals, a branch of steganography and steganalysis which has received much less attention than steganography and steganalysis for images. With this purpose in mind, it’s essential to get first a basic level of understanding of signal theory and the properties of the Human Auditory System, and we will dedicate ourselves to that aim during the first part of this work. Once established those basis, in the second part, we will obtain a precise image of the state of the art in steganographic and steganalytic sciences, from which we will be able to establish or deduce some good practices guides. With both previous subjects in mind, we will be able to create, design and implement a stego-system over Vorbis audio codec and, finally, as conclusion, analyze it using the principles studied during the first and second parts

Wavelet-Based Audio Embedding & Audio/Video Compression

With the decline in military spending, the United States relies heavily on state side support. Communications has never been more important. High-quality audio and video capabilities are a must. Watermarking, traditionally used for copyright protection, is used in a new and exciting way. An efficient wavelet-based watermarking technique embeds audio information into a video signal. Several highly effective compression techniques are applied to compress the resulting audio/video signal in an embedded fashion. This wavelet-based compression algorithm incorporates bit plane coding, first difference coding, and Huffman coding. To demonstrate the potential of this audio embedding audio/video compression system, an audio signal is embedded into a video signal and the combined signal is compressed. Results show that overall compression rates of 15:1 can be achieved. The video signal is reconstructed with a median PSNR of nearly 33dB. Finally, the audio signal is extracted with out error

Frame-synchronous Blind Audio Watermarking for Tamper Proofing and Self-Recovery

This paper presents a lifting wavelet transform (LWT)-based blind audio watermarking scheme designed for tampering detection and self-recovery. Following 3-level LWT decomposition of a host audio, the coefficients in selected subbands are first partitioned into frames for watermarking. To suit different purposes of the watermarking applications, binary information is packed into two groups: frame-related data are embedded in the approximation subband using rational dither modulation; the source-channel coded bit sequence of the host audio is hidden inside the 2nd and 3rd -detail subbands using 2N-ary adaptive quantization index modulation. The frame-related data consists of a synchronization code used for frame alignment and a composite message gathered from four adjacent frames for content authentication. To endow the proposed watermarking scheme with a self-recovering capability, we resort to hashing comparison to identify tampered frames and adopt a Reed–Solomon code to correct symbol errors. The experiment results indicate that the proposed watermarking scheme can accurately locate and recover the tampered regions of the audio signal. The incorporation of the frame synchronization mechanism enables the proposed scheme to resist against cropping and replacement attacks, all of which were unsolvable by previous watermarking schemes. Furthermore, as revealed by the perceptual evaluation of audio quality measures, the quality degradation caused by watermark embedding is merely minor. With all the aforementioned merits, the proposed scheme can find various applications for ownership protection and content authentication

ИНТЕЛЛЕКТУАЛЬНЫЙ числовым программным ДЛЯ MIMD-компьютер

For most scientific and engineering problems simulated on computers the solving of problems of the computational mathematics with approximately given initial data constitutes an intermediate or a final stage. Basic problems of the computational mathematics include the investigating and solving of linear algebraic systems, evaluating of eigenvalues and eigenvectors of matrices, the solving of systems of non-linear equations, numerical integration of initial- value problems for systems of ordinary differential equations.Для більшості наукових та інженерних задач моделювання на ЕОМ рішення задач обчислювальної математики з наближено заданими вихідними даними складає проміжний або остаточний етап. Основні проблеми обчислювальної математики відносяться дослідження і рішення лінійних алгебраїчних систем оцінки власних значень і власних векторів матриць, рішення систем нелінійних рівнянь, чисельного інтегрування початково задач для систем звичайних диференціальних рівнянь.Для большинства научных и инженерных задач моделирования на ЭВМ решение задач вычислительной математики с приближенно заданным исходным данным составляет промежуточный или окончательный этап. Основные проблемы вычислительной математики относятся исследования и решения линейных алгебраических систем оценки собственных значений и собственных векторов матриц, решение систем нелинейных уравнений, численного интегрирования начально задач для систем обыкновенных дифференциальных уравнений

Utilizing psychoacoustic model and Wavelet Packet Transform for purposes of audio signal watermarking

Tato diplomová práce pojednává o metodě prosazující dodržování vlastnických práv a ochranu multimediálních dat proti nelegální manipulaci s jeho obsahem – Digitálním vodoznačením audio signálů. Hlavním cílem této práce je implementovat algoritmus pro digitální vodoznačení audio dat. V teoretické části jsou popsány základní pojmy, metody a postupy, které se vztahují k této oblasti digitálního zpracování dat. V praktické části je realizován samotný proces vkládání tajné informace do originálního audia a následná možnost jejího zpětného vyjmutí. Algoritmus vodoznačení využívá metodu rozprostřeného spektra a psychoakustický model. Implementovaný psychoakustický model zahrnuje nedokonalosti lidského ucha, konkrétně jde o frekvenční maskování a dělení frekvenčního intervalu na kritická pásma. Tento model je založený na transformaci DWPT. Pomocí něho je vodoznak vkládán ke koeficientům vlnkové transformace ve vlnkové oblasti. Algoritmus vkládání a extrakce vodoznaku je implementován v programovém prostředí MATLAB. Část práce se zabývá testem robustnosti vloženého vodoznaku. Jsou použity běžné metody zpracování audio signálů: oříznutí audia, změna vzorkovacího kmitočtu, ztrátová komprese, filtrace, ekvalizace, vložení hudebního efektu a bílého šumu. V závěru diplomové práce jsou použity objektivní a subjektivní metody stanovení úrovně transparentnosti vloženého vodoznaku.This Thesis deals with a method to enforce the intellectual property rights and protect digital media from tampering – Digital Audio Watermarking. The main aim of this work is implement an audio watermarking algorithm. The theoretical part defined basic terms, methods and processes, which are used in this area. The practical part shows a process of embedding the digital signature into a host signal and her backward extraction. The embedding rule used spread spectrum technique and a psychoacoustic model. The implemented psychoacoustic model involves two properties of the human auditory system which are frequency masking and representation the frequency scale on limited bands called critical bands. The model is relatively new and based on the DWPT. In terms of above model is then the digital watermark embedded in the wavelet domain. This algorithm is implemented in technical software MATLAB. One part of this work focuses on robustness tests of the algorithm. Common signal processing modifications are applied to the watermarked audio as follows: Cutting of the audio, re-sampling, lossy compression, filtering, equalization, modulation effects, noise addition. The last part of the thesis presents subjective and objective methods usable in order to judge the influence of watermarking embedding on the quality of audio tracks called transparency.

Watermarking via zero assigned filter banks

Cataloged from PDF version of article.A watermarking scheme for audio and image files is proposed based on wavelet decomposition via zero assigned filter banks. Zero assigned filter banks are perfect reconstruction, conjugate quadrature mirror filter banks with assigned zeros in low pass and high pass filters. They correspond to a generalization of filter banks that yield Daubechies wavelets. The watermarking method consists of partitioning a given time or space signal into frames of fixed size, wavelet decomposing each frame via one of two filter banks with different assigned zeros, compressing a suitable set of coefficients in the wavelet decomposition, and reconstructing the signal from the compressed coefficients of frames. In effect, this method encodes the bit ‘0’ or ‘1’ in each frame depending on the filter bank that is used in the wavelet decomposition of that frame. The method is shown to be perceptually transparent and robust against channel noise as well as against various attacks to remove the watermark such as denoising, estimation, and compression. Moreover, the original signal is not needed for detection and the bandwidth requirement of the multiple authentication keys that are used in this method is very modest.Yücel, ZeynepM.S