Digital audio, video, images, and documents are flying through cyberspace to their respective owners. Unfortunately, along the way, individuals may choose to intervene and take this content for themselves. Digital watermarking and steganography technology greatly reduces the instances of this by limiting or eliminating the ability of third parties to decipher the content that he has taken. The many techiniques of digital watermarking (embedding a code) and steganography (hiding information) continue to evolve as applications that necessitate them do the same. The authors of this second edition provide an update on the framework for applying these techniques that they provided researchers and professionals in the first well-received edition. Steganography and steganalysis (the art of detecting hidden information) have been added to a robust treatment of digital watermarking, as many in each field research and deal with the other. New material includes watermarking with side information, QIM, and dirty-paper codes. The revision and inclusion of new material by these influential authors has created a must-own book for anyone in this profession.

*This new edition now contains essential information on steganalysis and steganography
*New concepts and new applications including QIM introduced
*Digital watermark embedding is given a complete update with new processes and applications

Digital Watermarking and Steganography

Digital Coding of Waveforms

During the last decade, CD-quality digital audio has essentially replaced analog audio. Emerging digital audio applications for network, wireless, and multimedia computing systems face a series of constraints such as reduced channel bandwidth, limited storage capacity, and low cost. These new applications have created a demand for high-quality digital audio delivery at low bit rates. In response to this need, considerable research has been devoted to the development of algorithms for perceptually transparent coding of high-fidelity (CD-quality) digital audio. As a result, many algorithms have been proposed, and several have now become international and/or commercial product standards. This paper reviews algorithms for perceptually transparent coding of CD-quality digital audio, including both research and standardization activities. This paper is organized as follows. First, psychoacoustic principles are described, with the MPEG psychoacoustic signal analysis model 1 discussed in some detail. Next, filter bank design issues and algorithms are addressed, with a particular emphasis placed on the modified discrete cosine transform, a perfect reconstruction cosine-modulated filter bank that has become of central importance in perceptual audio coding. Then, we review methodologies that achieve perceptually transparent coding of FM- and CD-quality audio signals, including algorithms that manipulate transform components, subband signal decompositions, sinusoidal signal components, and linear prediction parameters, as well as hybrid algorithms that make use of more than one signal model. These discussions concentrate on architectures and applications of those techniques that utilize psychoacoustic models to exploit efficiently masking characteristics of the human receiver. Several algorithms that have become international and/or commercial standards receive in-depth treatment, including the ISO/IEC MPEG family (-1, -2, -4), the Lucent Technologies PAC/EPAC/MPAC, the Dolby AC-2/AC-3, and the Sony ATRAC/SDDS algorithms. Then, we describe subjective evaluation methodologies in some detail, including the ITU-R BS.1116 recommendation on subjective measurements of small impairments. This paper concludes with a discussion of future research directions.

/pdf/perceptual-coding-of-digital-audio-1qcsomga6n.pdf

Perceptual coding of digital audio

Imagine the following situation. You’re in your car, listening to the radio and suddenly you hear a song that catches your attention. It’s the best new song you have heard for a long time, but you missed the announcement and don’t recognize the artist. Still, you would like to know more about this music. What should you do? You could call the radio station, but that’s too cumbersome. Wouldn’t it be nice if you could push a few buttons on your mobile phone and a few seconds later the phone would respond with the name of the artist and the title of the music you’re listening to? Perhaps even sending an email to your default email address with some supplemental information. In this paper we present an audio fingerprinting system, which makes the above scenario possible. By using the fingerprint of an unknown audio clip as a query on a fingerprint database, which contains the fingerprints of a large library of songs, the audio clip can be identified. At the core of the presented system are a highly robust fingerprint extraction method and a very efficient fingerprint search strategy, which enables searching a large fingerprint database with only limited computing resources.

https://ismir2002.ismir.net/proceedings/02-FP04-2.pdf

A Highly Robust Audio Fingerprinting System.

Binaural Cue Coding (BCC) is a method for multichannel spatial rendering based on one down-mixed audio channel and side information. The companion paper (Part I) covers the psychoacoustic fundamentals of this method and outlines principles for the design of BCC schemes. The BCC analysis and synthesis methods of Part I are motivated and presented in the framework of stereophonic audio coding. This paper, Part II, generalizes the basic BCC schemes presented in Part I. It includes BCC for multichannel signals and employs an enhanced set of perceptual spatial cues for BCC synthesis. A scheme for multichannel audio coding is presented. Moreover, a modified scheme is derived that allows flexible rendering of the spatial image at the receiver supporting dynamic control. All aspects of complete BCC encoder and decoder implementations are discussed, such as down-mixing of the input signals, low complexity estimation of the spatial cues, and quantization and coding of the side information. Application examples are given and the performance of the coder implementations are evaluated and discussed based on subjective listening test results.

/pdf/binaural-cue-coding-part-ii-schemes-and-applications-39qaaj3pak.pdf

Binaural cue coding-Part II:Schemes and applications

Inappropriate temporal spread of quantization noise is known to be the reason for the so-called \"pre-echo\" artifacts in perceptual audio coding. These artifacts occur when a transient signal is being coded in a spectral representation because the quantization noise is spread out over the entire window length of the filterbank and in this way is not masked by the signal. A novel approach to the pre-echo problem is presented allowing to shape the quantization noise in time. The technique is shown to work efficiently also in the case of \"pitched\" signals (e.g. speech) where traditional block switching schemes do not offer an efficient solution.

Enhancing the Performance of Perceptual Audio Coders by Using Temporal Noise Shaping (TNS)

In 2004 the ISO/MPEG Audio standardization group started a new work item on efficient and backward-compatible coding of high-quality multichannel sound using parametric coding techniques. Finalized in the fall of 2006, the resulting MPEG Surround specification allows the transmission of surround sound at bit rates that have been commonly used for coding of mono or stereo sound. The results of the standardization process are summarized by describing the underlying ideas and providing an overview of the MPEG Surround technology. The performance of the scheme is characterized by the results of recent verification tests. These tests include several operation modes as they would be used in typical application scenarios to introduce multichannel audio into existing audio services.

/pdf/mpeg-surround-the-iso-mpeg-standard-for-efficient-and-3rognjg23n.pdf

MPEG Surround – the ISO/MPEG Standard for Efficient and Compatible Multi-Channel Audio Coding

For a long time, many popular listening test methods, such as ITU-R BS.1534 (MUSHRA), could not be carried out as web-based listening tests, since established web standards did not support all required audio processing features. With the standardization of the Web Audio API, the required features became available and, therefore, also the possibility to implement a wide range of established methods as web-based listening tests. In order to simplify the implementation of MUSHRA listening tests, the development of webMUSHRA was started. By utilizing webMUSHRA, experimenters can configure web-based MUSHRA listening tests without the need of web programming expertise. Today, webMUSHRA supports many more listening test methods, such as ITU-R BS.1116 and forced-choice procedures. Moreover, webMUSHRA is highly customizable and has been used in many auditory studies for different purposes.

/pdf/webmushra-a-comprehensive-framework-for-web-based-listening-1r3a238uep.pdf

webMUSHRA — A Comprehensive Framework for Web-based Listening Tests

The invention relates to a method for coding or de-coding an audio signal combining the advantages of TNS processing and noise substitution. A time discrete audio signal is initially transformed in a frequency range in order to obtain spectral value of the temporal audio signal. A prediction of the spectral values in relation to frequency is subsequently made in order to enable spectral residual values. Areas within the spectral values encompassing spectral values with noise properties are detected . The spectral residual values are noise substituted in the noise areas, whereupon data relating to the noise areas and noise substitution are incorporated into side information pertaining to a coded audio signal.

Jürgen Herre

Papers

Enhancing the Performance of Perceptual Audio Coders by Using Temporal Noise Shaping (TNS)

MPEG Surround – the ISO/MPEG Standard for Efficient and Compatible Multi-Channel Audio Coding

webMUSHRA — A Comprehensive Framework for Web-based Listening Tests

Method for coding an audio signal

AudioID: Towards Content-Based Identification of Audio Material