Nikos Deligiannis

Side-Information-Dependent Correlation Channel Estimation in Hash-Based Distributed Video Coding

In the context of low-cost video encoding, distributed video coding (DVC) has recently emerged as a potential candidate for uplink-oriented applications. This paper builds on a concept of correlation channel (CC) modeling, which expresses the correlation noise as being statistically dependent on the side information (SI). Compared with classical side-information-independent (SII) noise modeling adopted in current DVC solutions, it is theoretically proven that side-information-dependent (SID) modeling improves the Wyner-Ziv coding performance. Anchored in this finding, this paper proposes a novel algorithm for online estimation of the SID CC parameters based on already decoded information. The proposed algorithm enables bit-plane-by-bit-plane successive refinement of the channel estimation leading to progressively improved accuracy. Additionally, the proposed algorithm is included in a novel DVC architecture that employs a competitive hash-based motion estimation technique to generate high-quality SI at the decoder. Experimental results corroborate our theoretical gains and validate the accuracy of the channel estimation algorithm. The performance assessment of the proposed architecture shows remarkable and consistent coding gains over a germane group of state-of-the-art distributed and standard video codecs, even under strenuous conditions, i.e., large groups of pictures and highly irregular motion content.

Compressed sensing with side information: Geometrical interpretation and performance bounds

We address the problem of Compressed Sensing (CS) with side information. Namely, when reconstructing a target CS signal, we assume access to a similar signal. This additional knowledge, the side information, is integrated into CS via ℓ₁-ℓ₁ and ℓ₁-ℓ₂ minimization. We then provide lower bounds on the number of measurements that these problems require for successful reconstruction of the target signal. If the side information has good quality, the number of measurements is significantly reduced via ℓ₁-ℓ₁ minimization, but not so much via ℓ₁-ℓ₂ minimization. We provide geometrical interpretations and experimental results illustrating our findings.

Overlapped Block Motion Estimation and Probabilistic Compensation with Application in Distributed Video Coding

It has been recently demonstrated that, in distributed video coding (DVC) side-information dependent modeling of the correlation channel brings significant performance gains over side-information independent assumptions. In this letter, we present a novel technique enabling advanced side-information dependent estimation of the correlation channel at the decoder starting from a very coarse knowledge of it. The proposed technique triggers the design of a spatial-domain DVC codec which enables the suppression of the feedback channel. Experimental results show that the proposed codec achieves similar performance compared to the state-of-the-art in transform-domain Wyner-Ziv video coding while still operating at a fraction of its encoding complexity.

Decentralized Time-Synchronized Channel Swapping for Ad Hoc Wireless Networks

Time-synchronized channel hopping (TSCH) is currently the most efficient solution for collision-free interference-avoiding communications in ad hoc wireless networks, such as wireless sensor networks, vehicular networks, and networks of robots or drones. However, all variants of TSCH require some form of centralized coordination to maintain the time-frequency slotting mechanism. This leads to slow convergence to steady state and moderate time-frequency slot utilization, particularly under node churn or mobility. We propose decentralized time-synchronized channel swapping (DT-SCS), which is a novel protocol for medium access control (MAC) in ad hoc wireless networks. Under the proposed protocol, nodes first converge to synchronous beacon packet transmissions across all available channels at the physical layer, with a balanced number of nodes in each channel. This is done by the novel coupling of distributed synchronization and desynchronization mechanisms-which are based on the concept of pulse-coupled oscillators-at the MAC layer. Decentralized channel swapping can then take place via peer-to-peer swap requests/acknowledgments made between concurrent transmitters in neighboring channels. We benchmark the convergence and network throughput of DT-SCS, TSCH, and the efficient multichannel MAC protocol (seen as the state of the art in decentralized, interference-avoiding, and multichannel MAC protocols) under simulated packet losses at the MAC layer. Moreover, performance results via a Contiki-based deployment on TelosB motes reveal that DT-SCS comprises an excellent candidate for decentralized multichannel MAC-layer coordination by providing for quick convergence to steady state, high bandwidth utilization under interference and hidden nodes, as well as high connectivity.

Rate-distortion driven decoder-side bitplane mode decision for distributed video coding

Distributed video coding (DVC) features simple encoders but complex decoders, which lies in contrast to conventional video compression solutions such as H.264/AVC. This shift in complexity is realized by performing motion estimation at the decoder side instead of at the encoder, which brings a number of problems that need to be dealt with. One of these problems is that, while employing different coding modes yields significant coding gains in classical video compression systems, it is still difficult to fully exploit this in DVC without increasing the complexity at the encoder side. Therefore, in this paper, instead of using an encoder-side approach, techniques for decoder-side mode decision are proposed. A rate-distortion model is derived that takes into account the position of the side information in the quantization bin. This model is then used to perform mode decision at the coefficient level and bitplane level. Average rate gains of 13-28% over the state-of-the-art DISCOVER codec are reported, for a GOP of size four, for several test sequences.

Dynamic sparse state estimation using ℓ 1 -ℓ 1 minimization: Adaptive-rate measurement bounds, algorithms and applications

We propose a recursive algorithm for estimating time-varying signals from a few linear measurements. The signals are assumed sparse, with unknown support, and are described by a dynamical model. In each iteration, the algorithm solves an ℓ1-ℓ1 minimization problem and estimates the number of measurements that it has to take at the next iteration. These estimates are computed based on recent theoretical results for ℓ1-ℓ1 minimization. We also provide sufficient conditions for perfect signal reconstruction at each time instant as a function of an algorithm parameter. The algorithm exhibits high performance in compressive tracking on a real video sequence, as shown in our experimental results.

Efficient Low-Delay Distributed Video Coding

Distributed video coding (DVC) is a video coding paradigm that allows for a low-complexity encoding process by exploiting the temporal redundancies in a video sequence at the decoder side. State-of-the-art DVC systems exhibit a structural coding delay since exploiting the temporal redundancies through motion-compensated interpolation requires the frames to be decoded out of order. To alleviate this problem, we propose a system based on motion-compensated extrapolation that allows for efficient low-delay video coding with low complexity at the encoder. The proposed extrapolation technique first estimates the motion field between the two most recently decoded frames using the Lucas-Kanade algorithm. The obtained motion field is then extrapolated to the current frame using an extrapolation grid. The proposed techniques are implemented into a novel architecture featuring hybrid block-frequency Wyner-Ziv coding as well as mode decision. Results show that having references from both temporal directions in interpolation provides superior rate-distortion performance over a single temporal direction in extrapolation, as expected. However, the proposed extrapolation method is particularly suitable for low-delay coding as it performs better than H.264/AVC intra, and it is even able to outperform the interpolation-based DVC codec from DISCOVER for several sequences.

Distributed coding of endoscopic video

Triggered by the challenging prerequisites of wireless capsule endoscopic video technology, this paper presents a novel distributed video coding (DVC) scheme, which employs an original hash-based side-information creation method at the decoder. In contrast to existing DVC schemes, the proposed codec generates high quality side-information at the decoder, even under the strenuous motion conditions encountered in endoscopic video. Performance evaluation using broad endoscopic video material shows that the proposed approach brings notable and consistent compression gains over various state-of-the-art video codecs at the additional benefit of vastly reduced encoding complexity.

Adaptive-Rate Reconstruction of Time-Varying Signals With Application in Compressive Foreground Extraction

We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown support, and evolve over time according to a generic nonlinear dynamical model. Our algorithm, based on recent theoretical results for l1 - l1 minimization, is recursive and computes the number of measurements to be taken at each time on-the-fly. As an example, we apply the algorithm to online compressive video foreground extraction, a problem stated as follows: given a set of measurements of a sequence of images with a static background, simultaneously reconstruct each image while separating its foreground from the background. The performance of our method is illustrated on sequences of real images. We observe that it allows a dramatic reduction in the number of measurements or reconstruction error with respect to state-of-the-art compressive background subtraction schemes.

Wyner-Ziv video coding for wireless lightweight multimedia applications

Wireless video communications promote promising opportunities involving commercial applications on a grand scale as well as highly specialized niche markets. In this regard, the design of efficient video coding systems, meeting such key requirements as low power, mobility and low complexity, is a challenging problem. The solution can be found in fundamental information theoretic results, which gave rise to the distributed video coding (DVC) paradigm, under which lightweight video encoding schemes can be engineered. This article presents a new hash-based DVC architecture incorporating a novel motion-compensated multi-hypothesis prediction technique. The presented method is able to adapt to the regional variations in temporal correlation in a frame. The proposed codec enables scalable Wyner-Ziv video coding and provides state-of-the-art distributed video compression performance. The key novelty of this article is the expansion of the application domain of DVC from conventional video material to medical imaging. Wireless capsule endoscopy in particular, which is essentially wireless video recording in a pill, is proven to be an important application field. The low complexity encoding characteristics, the ability of the novel motion-compensated multi-hypothesis prediction technique to adapt to regional degrees of temporal correlation (which is of crucial importance in the context of endoscopic video content), and the high compression performance make the proposed distributed video codec a strong candidate for future lightweight (medical) imaging applications.