Statistical Digital Watermarks of Audio Signals

Розроблені алгоритми вбудовування і виявлення цифрових водяних знаків в звукові сигнали на основі аналізу ковзаючого фрейма у частотній області. Алгоритми забезпечують мінімізацію спотворень сигналу, виявлення і декодування ЦВЗ в асинхронному режимі без використання яких-небудь маркерів і синхросигналів. Для забезпечення завадостійкості ЦВЗ застосована вузькосмугова багатоканальна передача і завадостійке кодування.Introduction. Digital watermarks (DWM) refer to embedding additional information directly into audio signal for digital right management and automatic identification of radiotelephone transmissions in aeronautical, maritime and military VHF communication. The main part. The designed embedding algorithm is based on evaluation of sliding frame to embed information or no regarding to distortions introduced by DWM. Watermark location is grounded calculation of distances norm between received and maximum likelihood estimated signal vectors in the domain of Discreet Fourier Transform and doesn’t need for any marking and synchronizing measures. Robustness of DWM against quantization, filtering, additive Gaussian noise, digital format conversion is provided by multichannel narrowband DWM transmission and application of BCH (63,30,6) error-correction code. The proposed algorithm demonstrates watermark inaudibility because of preserving signal power before and after data embedding and searching the most suitable frames for DWM positioning. Conclusion. The proposed algorithms provide advanced compromising solution of audio watermarking process: data payload – inaudibility – robustness. The designed algorithms are applicable both in analog and digital channels for transmission monitoring and digital right management.Разработаны алгоритмы встраивания и обнаружения цифровых водяных знаков в звуковые сигналы на основе анализа скользящего фрейма в частотной области. Алгоритмы обеспечивают минимизацию искажений сигнала, обнаружение и декодирование ЦВЗ в асинхронном режиме без использования каких-либо маркеров и синхросигналов. Для обеспечения помехоустойчивости ЦВЗ применена узкополосная многоканальная передача и помехоустойчивое кодирование

반향 환경에 강인한 음향 데이터 전송을 위한 오디오 정보 은닉 기법 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 김남수.In this dissertation, audio data hiding methods suitable for acoustic data transmission are studied. Acoustic data transmission implies a technique which communicates data in short-range aerial space between a loudspeaker and a microphone. Audio data hiding method implies a technique that embeds message signals into audio such as music or speech. The audio signal with embedded message is played back by the loudspeaker at a transmitter and the signal is recorded by the microphone at a receiver without any additional communication devices. The data hiding methods for acoustic data transmission require a high level of robustness and data rate than those for other applications. For one of the conventional methods, the acoustic orthogonal frequency division multiplexing (AOFDM) technique was developed as a reliable communication with reasonable bit rate. The conventional methods including AOFDM, however, are considered deficient in transmission performance or audio quality. To overcome this limitation, the modulated complex lapped transform (MCLT) is introduced in the second chapter of the dissertation. The system using MCLT does not produce blocking artifacts which may degrade the quality of the resulting data-embedded audio signal. Moreover, the interference among adjacent coefficients due to the overlap property is analyzed to take advantage of it for data embedding and extraction. In the third chapter of the dissertation, a novel audio data hiding method for the acoustic data transmission using MCLT is proposed. In the proposed system, audio signal is transformed by the MCLT and the phases of the coefficients are modified to embed message based on the fact that human auditory perception is more sensitive to the variation in magnitude spectra. In the proposed method, the perceived quality of the data-embedded audio signal can be kept almost similar to that of the original audio while transmitting data at several hundreds of bits per second (bps). The experimental results have shown that the audio quality and transmission performance of proposed system are better than those of the AOFDM based system. Moreover, several techniques have been found to further improve the performance of the proposed acoustic data transmission system which are listed as follows: incorporating a masking threshold (MM), clustering based decoding (CLS), and a spectral magnitude adjustment (SMA). In the fourth chapter of the dissertation, an audio data hiding technique more suitable for acoustic data transmission in reverberant environments is proposed. In this approach, sophisticated techniques widely deployed in wireless communication is incorporated which can be summarized as follows: First, a proper range of MCLT length to cope with reverberant environments is analyzed based on the wireless communication theory. Second, a channel estimation technique based on the Wiener estimator to compensate the effect of channel is applied in conjunction with a suitable data packet structure. From the experimental result, the MCLT length longer than the reverberation time is found to be robust against the reverberant environments at the cost of the quality of the data-embedded audio. The experimental results have also shown that the proposed method is robust against various forms of attacks such as signal processing, overwriting, and malicious removal methods. However, it would be the most severe problem to find a proper window length which satisfies both the inaudible distortion and robust data transmission in the reverberant environments. For the phase modification of the audio signal, it would be highly likely to incur a significant quality degradation if the length of time-frequency transform is very long due to the pre-echo phenomena. In the fifth chapter, therefore, segmental SNR adjustment (SSA) technique is proposed to further modify the spectral components for attenuating the pre-echo. In the proposed SSA technique, segmenatal SNR is calculated from short-length MCLT analysis and its minimum value is limited to a desired value. The experimental results have shown that the SSA algorithm with a long MCLT length can attenuate the pre-echo effectively such that it can transmit data more reliably while preserving good audio quality. In addition, a good trade-off between the audio quality and transmission performance can be achieved by adjusting only a single parameter in the SSA algorithm. If the number of microphones is more than one, the diversity technique which takes advantage of transmitting duplicates through statistically independent channel could be useful to enhance the transmission reliability. In the sixth chapter, the acoustic data transmission technique is extended to take advantage of the multi-microphone scheme based on combining. In the combining-based multichannel method, the synchronization and channel estimation are respectively performed at each received signal and then the received signals are linearly combined so that the SNR is increased. The most noticeable property for combining-based technique is to provide compatibility with the acoustic data transmission system using a single microphone. From the series of the experiments, the proposed multichannel method have been found to be useful to enhance the transmission performance despite of the statistical dependency between the channels.Abstract i List of Figures ix List of Tables xv Chapter 1 Introduction 1 1.1 Audio Data Hiding and Acoustic Data Transmission 1 1.2 Previous Methods 4 1.2.1 Audio Watermarking Based Methods 4 1.2.2 Wireless Communication Based Methods 6 1.3 Performance Evaluation 9 1.3.1 Audio Quality 9 1.3.2 Data Transmission Performance 10 1.4 Outline of the Dissertation 10 Chapter 2 Modulated Complex Lapped Transform 13 2.1 Introduction 13 2.2 MCLT 14 2.3 Fast Computation Algorithm 18 2.4 Derivation of Interference Terms in MCLT 19 2.5 Summary 24 Chapter 3 Acoustic Data Transmission Based on MCLT 25 3.1 Introduction 25 3.2 Data Embedding 27 3.2.1 Message Frame 27 3.2.2 Synchronization Frame 29 3.2.3 Data Packet Structure 32 3.3 Data Extraction 32 3.4 Techniques for Performance Enhancement 33 3.4.1 Magnitude Modification Based on Frequency Masking 33 3.4.2 Clustering-based Decoding 35 3.4.3 Spectral Magnitude Adjustment Algorithm 37 3.5 Experimental Results 39 3.5.1 Comparison with Acoustic OFDM 39 3.5.2 Performance Improvements by Magnitude Modification and Clustering based Decoding 47 3.5.3 Performance Improvements by Spectral Magnitude Adjustment 50 3.6 Summary 52 Chapter 4 Robust Acoustic Data Transmission against Reverberant Environments 55 4.1 Introduction 55 4.2 Data Embedding 56 4.2.1 Data Embedding 57 4.2.2 MCLT Length 58 4.2.3 Data Packet Structure 60 4.3 Data Extraction 61 4.3.1 Synchronization 61 4.3.2 Channel Estimation and Compensation 62 4.3.3 Data Decoding 65 4.4 Experimental Results 66 4.4.1 Robustness to Reverberation 69 4.4.2 Audio Quality 71 4.4.3 Robustness to Doppler Effect 71 4.4.4 Robustness to Attacks 71 4.5 Summary 75 Chapter 5 Segmental SNR Adjustment for Audio Quality Enhancement 77 5.1 Introduction 77 5.2 Segmental SNR Adjustment Algorithm 79 5.3 Experimental Results 83 5.3.1 System Configurations 83 5.3.2 Audio Quality Test 84 5.3.3 Robustness to Attacks 86 5.3.4 Transmission Performance of Recorded Signals in Indoor Environment 87 5.3.5 Error correction using convolutional coding 89 5.4 Summary 91 Chapter 6 Multichannel Acoustic Data Transmission 93 6.1 Introduction 93 6.2 Multichannel Techniques for Robust Data Transmission 94 6.2.1 Diversity Techniques for Multichannel System 94 6.2.2 Combining-based Multichannel Acoustic Data Transmission 98 6.3 Experimental Results 100 6.3.1 Room Environments 101 6.3.2 Transmission Performance of Simulated Environments 102 6.3.3 Transmission Performance of Recorded Signals in Reverberant Environment 105 6.4 Summary 106 Chapter 7 Conclusions 109 Bibliography 113 국문초록 121Docto

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Systematic hybrid analog/digital signal coding

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 201-206).This thesis develops low-latency, low-complexity signal processing solutions for systematic source coding, or source coding with side information at the decoder. We consider an analog source signal transmitted through a hybrid channel that is the composition of two channels: a noisy analog channel through which the source is sent unprocessed and a secondary rate-constrained digital channel; the source is processed prior to transmission through the digital channel. The challenge is to design a digital encoder and decoder that provide a minimum-distortion reconstruction of the source at the decoder, which has observations of analog and digital channel outputs. The methods described in this thesis have importance to a wide array of applications. For example, in the case of in-band on-channel (IBOC) digital audio broadcast (DAB), an existing noisy analog communications infrastructure may be augmented by a low-bandwidth digital side channel for improved fidelity, while compatibility with existing analog receivers is preserved. Another application is a source coding scheme which devotes a fraction of available bandwidth to the analog source and the rest of the bandwidth to a digital representation. This scheme is applicable in a wireless communications environment (or any environment with unknown SNR), where analog transmission has the advantage of a gentle roll-off of fidelity with SNR. A very general paradigm for low-latency, low-complexity source coding is composed of three basic cascaded elements: 1) a space rotation, or transformation, 2) quantization, and 3) lossless bitstream coding. The paradigm has been applied with great success to conventional source coding, and it applies equally well to systematic source coding. Focusing on the case involving a Gaussian source, Gaussian channel and mean-squared distortion, we determine optimal or near-optimal components for each of the three elements, each of which has analogous components in conventional source coding. The space rotation can take many forms such as linear block transforms, lapped transforms, or subband decomposition, all for which we derive conditions of optimality. For a very general case we develop algorithms for the design of locally optimal quantizers. For the Gaussian case, we describe a low-complexity scalar quantizer, the nested lattice scalar quantizer, that has performance very near that of the optimal systematic scalar quantizer. Analogous to entropy coding for conventional source coding, Slepian-Wolf coding is shown to be an effective lossless bitstream coding stage for systematic source coding.by Richard J. Barron.Ph.D

Inaudible acoustics: Techniques and applications

This dissertation is focused on developing a sub-area of acoustics that we call inaudible acoustics. We have developed two core capabilities, (1) BackDoor and (2) Ripple, and demonstrated their use in various mobile and IoT applications. In BackDoor, we synthesize ultrasound signals that are inaudible to humans yet naturally recordable by all microphones. Importantly, the microphone does not require any modification, enabling billions of microphone-enabled devices, including phones, laptops, voice assistants, and IoT devices, to leverage the capability. Example applications include acoustic data beacons, acoustic watermarking, and spy-microphone jamming. In Ripple, we develop modulation and sensing techniques for vibratory signals that traverse through solid surfaces, enabling a new form of secure proximal communication. Applications of the vibratory communication system include on-body communication through imperceptible physical vibrations and device-device secure data transfer through physical contacts. Our prototypes include an inaudible jammer that secures private conversations from electronic eavesdropping, acoustic beacons for location-based information sharing, and vibratory communication in a smart-ring sending password through a finger touch. Our research also uncovers new security threats to acoustic devices. While simple abuse of inaudible jammer can disable hearing aids and cell phones, our work shows that voice interfaces, such as Amazon Echo, Google Home, Siri, etc., can be compromised through carefully designed inaudible voice commands. The contributions of this dissertation can be summarized in three primitives: (1) exploiting inherent hardware nonlinearity for sensing out-of-band signals, (2) developing the vibratory communication system for secure touch-based data exchange, and (3) structured information reconstruction from noisy acoustic signals. In developing these primitives, we draw from principles in wireless networking, digital communications, signal processing, and embedded design and translate them to completely functional systems