Coding overcomplete representations of audio using the MCLT

We propose a system for audio coding using the modulated complex lapped transform (MCLT). In general, it is difficult to encode signals using overcomplete representations without avoiding a penalty in rate-distortion performance. We show that the penalty can be significantly reduced for MCLT-based representations, without the need for iterative methods of sparsity reduction. We achieve that via a magnitude-phase polar quantization and the use of magnitude and phase prediction. Compared to systems based on quantization of orthogonal representations such as the modulated lapped transform (MLT), the new system allows for reduced warbling artifacts and more precise computation of frequency-domain auditory masking functions

Efficiency in audio processing : filter banks and transcoding

Audio transcoding is the conversion of digital audio from one compressed form A to another compressed form B, where A and B have different compression properties, such as a different bit-rate, sampling frequency or compression method. This is typically achieved by decoding A to an intermediate uncompressed form, and then encoding it to B. A significant portion of the involved computational effort pertains to operating the synthesis filter bank, which is an important processing block in the decoding stage, and the analysis filter bank, which is an important processing block in the encoding stage. This thesis presents methods for efficient implementations of filter banks and audio transcoders, and is separated into two main parts. In the first part, a new class of Frequency Response Masking (FRM) filter banks is introduced. These filter banks are usually characterized by comprising a tree-structured cascade of subfilters, which have small individual filter lengths. Methods of complexity reduction are proposed for the scenarios when the filter banks are operated in single-rate mode, and when they are operated in multirate mode; and for the scenarios when the input signal is real-valued, and when it is complex-valued. An efficient variable bandwidth FRM filter bank is designed by using signed-powers-of-two reduction of its subfilter coefficients. Our design has a complexity an order lower than that of an octave filter bank with the same specifications. In the second part, the audio transcoding process is analyzed. Audio transcoding is modeled as a cascaded quantization process, and the cascaded quantization of an input signal is analyzed under different conditions, for the MPEG 1 Layer 2 and MP3 compression methods. One condition is the input-to-output delay of the transcoder, which is known to have an impact on the audio quality of the transcoded material. Methods to reduce the error in a cascaded quantization process are also proposed. An ultra-fast MP3 transcoder that requires only integer operations is proposed and implemented in software. Our implementation shows an improvement by a factor of 5 to 16 over other best known transcoders in terms of execution speed

Audio Coding Based on Integer Transforms

Die Audiocodierung hat sich in den letzten Jahren zu einem sehr populären Forschungs- und Anwendungsgebiet entwickelt. Insbesondere gehörangepasste Verfahren zur Audiocodierung, wie etwa MPEG-1 Layer-3 (MP3) oder MPEG-2 Advanced Audio Coding (AAC), werden häufig zur effizienten Speicherung und Übertragung von Audiosignalen verwendet. Für professionelle Anwendungen, wie etwa die Archivierung und Übertragung im Studiobereich, ist hingegen eher eine verlustlose Audiocodierung angebracht. Die bisherigen Ansätze für gehörangepasste und verlustlose Audiocodierung sind technisch völlig verschieden. Moderne gehörangepasste Audiocoder basieren meist auf Filterbänken, wie etwa der überlappenden orthogonalen Transformation "Modifizierte Diskrete Cosinus-Transformation" (MDCT). Verlustlose Audiocoder hingegen verwenden meist prädiktive Codierung zur Redundanzreduktion. Nur wenige Ansätze zur transformationsbasierten verlustlosen Audiocodierung wurden bisher versucht. Diese Arbeit präsentiert einen neuen Ansatz hierzu, der das Lifting-Schema auf die in der gehörangepassten Audiocodierung verwendeten überlappenden Transformationen anwendet. Dies ermöglicht eine invertierbare Integer-Approximation der ursprünglichen Transformation, z.B. die IntMDCT als Integer-Approximation der MDCT. Die selbe Technik kann auch für Filterbänke mit niedriger Systemverzögerung angewandt werden. Weiterhin ermöglichen ein neuer, mehrdimensionaler Lifting-Ansatz und eine Technik zur Spektralformung von Quantisierungsfehlern eine Verbesserung der Approximation der ursprünglichen Transformation. Basierend auf diesen neuen Integer-Transformationen werden in dieser Arbeit neue Verfahren zur Audiocodierung vorgestellt. Die Verfahren umfassen verlustlose Audiocodierung, eine skalierbare verlustlose Erweiterung eines gehörangepassten Audiocoders und einen integrierten Ansatz zur fein skalierbaren gehörangepassten und verlustlosen Audiocodierung. Schließlich wird mit Hilfe der Integer-Transformationen ein neuer Ansatz zur unhörbaren Einbettung von Daten mit hohen Datenraten in unkomprimierte Audiosignale vorgestellt.In recent years audio coding has become a very popular field for research and applications. Especially perceptual audio coding schemes, such as MPEG-1 Layer-3 (MP3) and MPEG-2 Advanced Audio Coding (AAC), are widely used for efficient storage and transmission of music signals. Nevertheless, for professional applications, such as archiving and transmission in studio environments, lossless audio coding schemes are considered more appropriate. Traditionally, the technical approaches used in perceptual and lossless audio coding have been separate worlds. In perceptual audio coding, the use of filter banks, such as the lapped orthogonal transform "Modified Discrete Cosine Transform" (MDCT), has been the approach of choice being used by many state of the art coding schemes. On the other hand, lossless audio coding schemes mostly employ predictive coding of waveforms to remove redundancy. Only few attempts have been made so far to use transform coding for the purpose of lossless audio coding. This work presents a new approach of applying the lifting scheme to lapped transforms used in perceptual audio coding. This allows for an invertible integer-to-integer approximation of the original transform, e.g. the IntMDCT as an integer approximation of the MDCT. The same technique can also be applied to low-delay filter banks. A generalized, multi-dimensional lifting approach and a noise-shaping technique are introduced, allowing to further optimize the accuracy of the approximation to the original transform. Based on these new integer transforms, this work presents new audio coding schemes and applications. The audio coding applications cover lossless audio coding, scalable lossless enhancement of a perceptual audio coder and fine-grain scalable perceptual and lossless audio coding. Finally an approach to data hiding with high data rates in uncompressed audio signals based on integer transforms is described

Audio Coding Based on Integer Transforms

Die Audiocodierung hat sich in den letzten Jahren zu einem sehr populären Forschungs- und Anwendungsgebiet entwickelt. Insbesondere gehörangepasste Verfahren zur Audiocodierung, wie etwa MPEG-1 Layer-3 (MP3) oder MPEG-2 Advanced Audio Coding (AAC), werden häufig zur effizienten Speicherung und Übertragung von Audiosignalen verwendet. Für professionelle Anwendungen, wie etwa die Archivierung und Übertragung im Studiobereich, ist hingegen eher eine verlustlose Audiocodierung angebracht. Die bisherigen Ansätze für gehörangepasste und verlustlose Audiocodierung sind technisch völlig verschieden. Moderne gehörangepasste Audiocoder basieren meist auf Filterbänken, wie etwa der überlappenden orthogonalen Transformation "Modifizierte Diskrete Cosinus-Transformation" (MDCT). Verlustlose Audiocoder hingegen verwenden meist prädiktive Codierung zur Redundanzreduktion. Nur wenige Ansätze zur transformationsbasierten verlustlosen Audiocodierung wurden bisher versucht. Diese Arbeit präsentiert einen neuen Ansatz hierzu, der das Lifting-Schema auf die in der gehörangepassten Audiocodierung verwendeten überlappenden Transformationen anwendet. Dies ermöglicht eine invertierbare Integer-Approximation der ursprünglichen Transformation, z.B. die IntMDCT als Integer-Approximation der MDCT. Die selbe Technik kann auch für Filterbänke mit niedriger Systemverzögerung angewandt werden. Weiterhin ermöglichen ein neuer, mehrdimensionaler Lifting-Ansatz und eine Technik zur Spektralformung von Quantisierungsfehlern eine Verbesserung der Approximation der ursprünglichen Transformation. Basierend auf diesen neuen Integer-Transformationen werden in dieser Arbeit neue Verfahren zur Audiocodierung vorgestellt. Die Verfahren umfassen verlustlose Audiocodierung, eine skalierbare verlustlose Erweiterung eines gehörangepassten Audiocoders und einen integrierten Ansatz zur fein skalierbaren gehörangepassten und verlustlosen Audiocodierung. Schließlich wird mit Hilfe der Integer-Transformationen ein neuer Ansatz zur unhörbaren Einbettung von Daten mit hohen Datenraten in unkomprimierte Audiosignale vorgestellt.In recent years audio coding has become a very popular field for research and applications. Especially perceptual audio coding schemes, such as MPEG-1 Layer-3 (MP3) and MPEG-2 Advanced Audio Coding (AAC), are widely used for efficient storage and transmission of music signals. Nevertheless, for professional applications, such as archiving and transmission in studio environments, lossless audio coding schemes are considered more appropriate. Traditionally, the technical approaches used in perceptual and lossless audio coding have been separate worlds. In perceptual audio coding, the use of filter banks, such as the lapped orthogonal transform "Modified Discrete Cosine Transform" (MDCT), has been the approach of choice being used by many state of the art coding schemes. On the other hand, lossless audio coding schemes mostly employ predictive coding of waveforms to remove redundancy. Only few attempts have been made so far to use transform coding for the purpose of lossless audio coding. This work presents a new approach of applying the lifting scheme to lapped transforms used in perceptual audio coding. This allows for an invertible integer-to-integer approximation of the original transform, e.g. the IntMDCT as an integer approximation of the MDCT. The same technique can also be applied to low-delay filter banks. A generalized, multi-dimensional lifting approach and a noise-shaping technique are introduced, allowing to further optimize the accuracy of the approximation to the original transform. Based on these new integer transforms, this work presents new audio coding schemes and applications. The audio coding applications cover lossless audio coding, scalable lossless enhancement of a perceptual audio coder and fine-grain scalable perceptual and lossless audio coding. Finally an approach to data hiding with high data rates in uncompressed audio signals based on integer transforms is described

Detection and localization of double compression in MP3 audio tracks

In this work, by exploiting the traces left by double compression in the statistics of quantized modified discrete cosine transform coefficients, a single measure has been derived that allows to decide whether an MP3 file is singly or doubly compressed and, in the last case, to devise also the bit-rate of the first compression. Moreover, the proposed method as well as two state-of-the-art methods have been applied to analyze short temporal windows of the track, allowing the localization of possible tampered portions in the MP3 file under analysis. Experiments confirm the good performance of the proposed scheme and demonstrate that current detection methods are useful for tampering localization, thus offering a new tool for the forensic analysis of MP3 audio tracks

Pixinwav: Residual steganography for hiding pixels in audio

Steganography comprises the mechanics of hiding data in a host media that may be publicly available. While previous works focused on unimodal setups (e.g., hiding images in images, or hiding audio in audio), PixInWav targets the multimodal case of hiding images in audio. To this end, we propose a novel residual architecture operating on top of short-time discrete cosine transform (STDCT) audio spectrograms. Among our results, we find that the residual steganography setup we propose allows an encoding of the hidden image that is independent from the host audio without compromising quality. Accordingly, while previous works require both host and hidden signals to hide a signal, PixInWav can encode images offline—which can be later hidden, in a residual fashion, into any audio signal.Work partially supported by the European Union through the Erasmus+ student mobility program, Science Foundation Ireland (SFI) under grant numbers SFI/15/SIRG/3283 and SFI/12/RC/2289 P2, and the Spanish Research Agency (AEI) under project PID2020117142GB-I00 of the call MCIN/ AEI /10.13039/501100011033.Peer ReviewedPostprint (author's final draft

Design of digital IP block for discrete cosine transform

Tato diplomová práce se zabývá návrhem IP bloku pro diskrétní kosinovou transformaci. V~teoretické části jsou shrnuty algoritmy pro výpočet diskrétní kosinové transformace a diskutována jejich použitelnost v~hardwaru. Zvolený algoritmus pro hardwarovou implementaci je modelován v jazyce C. Poté je popsán na RTL úrovni, verifikován a je provedena syntéza v~technologii TSMC 65 nm. Hardwarová implementace je poté zhodnocena s ohledem na datovou propustnost, plochu, rychlost and spotřebu.This diploma thesis deals with design of IP block for discrete cosine transform. Theoretical part summarizes algorithms for computation of discrete cosine transform and their hardware usability is discussed. Chosen algorithm for hardware implementation is modeled in C language. Algorithm is described at RTL level, verified and synthesized to TSMC 65 nm technology. Hardware implementation is then evaluated with respect of throughput, area, speed and power consumption.