Identification of Sparse Audio Tampering Using Distributed Source Coding and Compressive Sensing Techniques

In the past few years, a large amount of techniques have been proposed to identify whether a multimedia content has been illegally tampered or not. Nevertheless, very few efforts have been devoted to identifying which kind of attack has been carried out, especially due to the large data required for this task. We propose a novel hashing scheme which exploits the paradigms of compressive sensing and distributed source coding to generate a compact hash signature, and we apply it to the case of audio content protection. The audio content provider produces a small hash signature by computing a limited number of random projections of a perceptual, time-frequency representation of the original audio stream; the audio hash is given by the syndrome bits of an LDPC code applied to the projections. At the content user side, the hash is decoded using distributed source coding tools. If the tampering is sparsifiable or compressible in some orthonormal basis or redundant dictionary, it is possible to identify the time-frequency position of the attack, with a hash size as small as 200 bits/second; the bit saving obtained by introducing distributed source coding ranges between 20% to 70%

Selected topics on distributed video coding

Distributed Video Coding (DVC) is a new paradigm for video compression based on the information theoretical results of Slepian and Wolf (SW), and Wyner and Ziv (WZ). While conventional coding has a rigid complexity allocation as most of the complex tasks are performed at the encoder side, DVC enables a flexible complexity allocation between the encoder and the decoder. The most novel and interesting case is low complexity encoding and complex decoding, which is the opposite of conventional coding. While the latter is suitable for applications where the cost of the decoder is more critical than the encoder's one, DVC opens the door for a new range of applications where low complexity encoding is required and the decoder's complexity is not critical. This is interesting with the deployment of small and battery-powered multimedia mobile devices all around in our daily life. Further, since DVC operates as a reversed-complexity scheme when compared to conventional coding, DVC also enables the interesting scenario of low complexity encoding and decoding between two ends by transcoding between DVC and conventional coding. More specifically, low complexity encoding is possible by DVC at one end. Then, the resulting stream is decoded and conventionally re-encoded to enable low complexity decoding at the other end. Multiview video is attractive for a wide range of applications such as free viewpoint television, which is a system that allows viewing the scene from a viewpoint chosen by the viewer. Moreover, multiview can be beneficial for monitoring purposes in video surveillance. The increased use of multiview video systems is mainly due to the improvements in video technology and the reduced cost of cameras. While a multiview conventional codec will try to exploit the correlation among the different cameras at the encoder side, DVC allows for separate encoding of correlated video sources. Therefore, DVC requires no communication between the cameras in a multiview scenario. This is an advantage since communication is time consuming (i.e. more delay) and requires complex networking. Another appealing feature of DVC is the fact that it is based on a statistical framework. Moreover, DVC behaves as a natural joint source-channel coding solution. This results in an improved error resilience performance when compared to conventional coding. Further, DVC-based scalable codecs do not require a deterministic knowledge of the lower layers. In other words, the enhancement layers are completely independent from the base layer codec. This is called the codec-independent scalability feature, which offers a high flexibility in the way the various layers are distributed in a network. This thesis addresses the following topics: First, the theoretical foundations of DVC as well as the practical DVC scheme used in this research are presented. The potential applications for DVC are also outlined. DVC-based schemes use conventional coding to compress parts of the data, while the rest is compressed in a distributed fashion. Thus, different conventional codecs are studied in this research as they are compared in terms of compression efficiency for a rich set of sequences. This includes fine tuning the compression parameters such that the best performance is achieved for each codec. Further, DVC tools for improved Side Information (SI) and Error Concealment (EC) are introduced for monoview DVC using a partially decoded frame. The improved SI results in a significant gain in reconstruction quality for video with high activity and motion. This is done by re-estimating the erroneous motion vectors using the partially decoded frame to improve the SI quality. The latter is then used to enhance the reconstruction of the finally decoded frame. Further, the introduced spatio-temporal EC improves the quality of decoded video in the case of erroneously received packets, outperforming both spatial and temporal EC. Moreover, it also outperforms error-concealed conventional coding in different modes. Then, multiview DVC is studied in terms of SI generation, which differentiates it from the monoview case. More specifically, different multiview prediction techniques for SI generation are described and compared in terms of prediction quality, complexity and compression efficiency. Further, a technique for iterative multiview SI is introduced, where the final SI is used in an enhanced reconstruction process. The iterative SI outperforms the other SI generation techniques, especially for high motion video content. Finally, fusion techniques of temporal and inter-view side informations are introduced as well, which improves the performance of multiview DVC over monoview coding. DVC is also used to enable scalability for image and video coding. Since DVC is based on a statistical framework, the base and enhancement layers are completely independent, which is an interesting property called codec-independent scalability. Moreover, the introduced DVC scalable schemes show a good robustness to errors as the quality of decoded video steadily decreases with error rate increase. On the other hand, conventional coding exhibits a cliff effect as the performance drops dramatically after a certain error rate value. Further, the issue of privacy protection is addressed for DVC by transform domain scrambling, which is used to alter regions of interest in video such that the scene is still understood and privacy is preserved as well. The proposed scrambling techniques are shown to provide a good level of security without impairing the performance of the DVC scheme when compared to the one without scrambling. This is particularly attractive for video surveillance scenarios, which is one of the most promising applications for DVC. Finally, a practical DVC demonstrator built during this research is described, where the main requirements as well as the observed limitations are presented. Furthermore, it is defined in a setup being as close as possible to a complete real application scenario. This shows that it is actually possible to implement a complete end-to-end practical DVC system relying only on realistic assumptions. Even though DVC is inferior in terms of compression efficiency to the state of the art conventional coding for the moment, strengths of DVC reside in its good error resilience properties and the codec-independent scalability feature. Therefore, DVC offers promising possibilities for video compression with transmission over error-prone environments requirement as it significantly outperforms conventional coding in this case

Multiterminal Video Coding: From Theory to Application

Multiterminal (MT) video coding is a practical application of the MT source coding theory. For MT source coding theory, two problems associated with achievable rate regions are well investigated into in this thesis: a new sufficient condition for BT sum-rate tightness, and the sum-rate loss for quadratic Gaussian MT source coding. Practical code design for ideal Gaussian sources with quadratic distortion measure is also achieved for cases more than two sources with minor rate loss compared to theoretical limits. However, when the theory is applied to practical applications, the performance of MT video coding has been unsatisfactory due to the difficulty to explore the correlation between different camera views. In this dissertation, we present an MT video coding scheme under the H.264/AVC framework. In this scheme, depth camera information can be optionally sent to the decoder separately as another source sequence. With the help of depth information at the decoder end, inter-view correlation can be largely improved and thus so is the compression performance. With the depth information, joint estimation from decoded frames and side information at the decoder also becomes available to improve the quality of reconstructed video frames. Experimental result shows that compared to separate encoding, up to 9.53% of the bit rate can be saved by the proposed MT scheme using decoder depth information, while up to 5.65% can be saved by the scheme without depth camera information. Comparisons to joint video coding schemes are also provided

Cloud Radio Access Network in Constrained Fronthaul

The Cloud Radio Access Network (C-RAN) has been proposed for the provision of advanced fourth and fifth generation wireless communication services. The C-RAN system have been shown to reduce costs, and can provide high spectral efficiency and energy efficiency. The fronthaul in such networks, defined as the transmission links between Remote Radio Units (RRUs) and a central Baseband Unit (BBU), usually has high fronthaul load and constrained capacity. In this thesis, we explore and investigate the basic C-RAN system structure, based on which we propose two developed C-RAN systems. With each system we evaluate the Bit Error Ratio (BER) performance and transmission efficiency in multiple scenarios, and give advanced solutions to reduce the fronthaul load. We also analyse the effect of quantization on BPSK and QPSK modulation schemes, with different detection methods. Error control in fronthaul transmission is considered as erroneous frames may be received at the BBU. Error Detection Coding and Error Correction Coding approaches can be applied to the fronthaul network. They may increase the fronthaul latency, but great improve the end-to-end BER performance. Source compression techniques such as Slepian-Wolf (SW) coding can compress two correlated sources separately and de-compress them jointly. Since each RRU serves many user terminals, and some of them may also be served by another neighbour RRU, which results similarly in correlation of the received data between two RRUs. In this thesis, we applied the SW code to the C-RAN system and evaluate the compression rate achieved in fronthaul networks

Self-concatenated code design and its application in power-efficient cooperative communications

In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions