Description:
Cognitive radio network (CRN) users are inherently expected to experience widely-varied delays due to the uncertainty in wireless channel availability. Supporting delay sensitive real-time services through CRNs, so that visitors are allowed to experience full-scale networking services by opportunistically sharing the spectrum from a number of existing networks without impacting on the primary users, thus remains a challenging task. This paper presents a novel technique to provision QoS guarantee for delay-sensitive services in CRNs having secondary users equipped with multiple radio interfaces. The technique relies on modeling spectrums holes from multiple primary networks through a resultant channel to enable implementing a single server queuing model with random service interruption. Simulation results using ns-2.33 show that using multiple radio interfaces has sheer strength to reduce CRN delay with fewer number of primary channel sensing.
Description:
Algorithms using content-based patterns to segment moving regions at the macroblock (MB) level have exhibited good potential for improved coding efficiency when embedded into the H.264 standard as an extra mode. The content-based pattern generation (CPG) algorithm provides local optimal result as only one pattern can be optimally generated from a given set of moving regions. But, it failed to provide optimal results for multiple patterns from entire sets. Obviously, a global optimal solution for clustering the set and then generation of multiple patterns enhances the performance farther. But a global optimal solution is not achievable due to the non-polynomial nature of the clustering problem. In this paper, we propose a near-optimal content-based pattern generation (OCPG) algorithm which outperforms the existing approach. Coupling OCPG, generating a set of patterns after clustering the MBs into several disjoint sets, with a direct pattern selection algorithm by allowing all the MBs in multiple pattern modes outperforms the existing pattern-based coding when embedded into the H.264.
Description:
Algorithms using content-based patterns to segment moving regions at the macroblock (MB) level have exhibited good potential for improved coding efficiency when embedded into the H.264 standard as an extra mode. The content-based pattern generation (CPG) algorithm provides local optimal result as only one pattern can be optimally generated from a given set of moving regions. But, it failed to provide optimal results for multiple patterns from entire sets. Obviously, a global optimal solution for clustering the set and then generation of multiple patterns enhances the performance farther. But a global optimal solution is not achievable due to the non-polynomial nature of the clustering problem. In this paper, we propose a near-optimal content-based pattern generation (OCPG) algorithm which outperforms the existing approach. Coupling OCPG, generating a set of patterns after clustering the MBs into several disjoint sets, with a direct pattern selection algorithm by allowing all the MBs in multiple pattern modes outperforms the existing pattern-based coding when embedded into the H.264.
Description:
Abstract—Preserving privacy in participatory sensing systems has recently gained research interest as voluntary contribution in such systems is not worthy if the privacy of the participants is not protected. On the other hand, data integrity is desired imperatively to make the service trustworthy and user-friendly. In this paper, we have proposed an adaptive location anonymization technique, which is capable of retaining an acceptable level of data integrity while keeping its vulnerability to eavesdropping adversaries low. Experimental results establish the proposed concept as a superior approach in balancing, somehow orthogonal, user privacy and data integrity.
Description:
Color image fusion of visible and infra-red imagery can play an important role in multi-sensor night vision systems that are an integral part of modern warfare. Image fusion minimizes the amount of required bandwidth by transmitting the fused image rather than multiple sensor images. Color image fusion can be achieved by combining inputs from original colored sensors or by employing pseudo colorization and color transfer to grayscale images. Various quality measures have been proposed for multi-sensor grayscale image fusion techniques; but no appropriate quality measure has been devised for the quality evaluation of multi-sensor color image fusion. In this paper, we propose a novel color image fusion quality measure, Color Fusion Objective Index (CFOI) based on colorfulness, gradient similarity and mutual information techniques. Experimental results show the effectiveness of CFOI to evaluate the color and salient feature extraction introduced by color fusion techniques into the final fused imagery as well as its consistency with subjective evaluation.
Description:
In a decentralized sensor network, localization process relies on the integrity of participating sensors. Existence of malicious beacon nodes in the vicinity of non-beacon nodes affects this process. This paper presents a trilateration-based secure localization technique, which is capable of estimating the location of a sensor with high accuracy so long four neighbouring beacon nodes are benign, irrespective of the number of neighbouring liars and without assuming any trust model. In realistic scenarios of wireless environment where transmitted signals attenuate randomly due to fading, the liar-tolerance level of this attack-resistant technique has to be relaxed accordingly. Superiority of this technique against the state-of-the-art has been established with extensive simulation results in terms of location estimation accuracy and liar-filtering probability.
Description:
In this paper, we present an automated color transfer based video fusion method to attain real-time color night vision capability for night-time video surveillance. We utilize simple RGB Color transfer technique to fused pseudo colored video frames without conversion to any uncorrelated color space. We investigated that final color fusion results greatly depend on the selection of target color Image. Therefore, rather than using any arbitrary target color image based on mere general visual anticipation, we have automated target color image selection using structural similarity and color saturation. We further apply color enhancement to improve final appearance of color fused images. Subjective and objective quality evaluations greatly indicate the effectiveness of our color video fusion method for nighttime video surveillance applications.
Description:
Due to the infrequent medium access in Wireless Sensor Networks (WSN), their MAC protocols are mostly based on CSMA. In this paper we present an efficient contention resolution scheme for CSMA based MAC protocols which is suitable for periodic data collection in WSNs. Taking into account that the number of nodes in a single cluster is fixed, this protocol uses successively decreasing contention window. It is characterized by non-overlapping contention window, that maintains a constant successful transmission rate. It significantly decreases data collection time by minimizing the time wastage due to collisions. At the same time, by using adaptive CW, it reduces the time wastage in empty slots. Experimental results demonstrate that in periodic data collection within a single hop cluster this scheme has performance superior to the recently proposed Synchronous Shared Contention Window (SSCW) based scheme in terms of time wastage and throughput.
Description:
In this paper, we discuss the problems associated with the present contention resolution mechanism of IEEE 802.11 DCF and present a new, dynamic and robust approach to improve it. Our new MAC, using OFDMA in the physical layer, can incorporate multiple concurrent transmissions or receptions in a dynamic manner and can adjust the collision probability based on the traffic load when nodes are endowed with a single half-duplex radio only. Simulation results show that our system improves throughput by up to 40 percent, reduces collision in control messages by up to 80 percent and reduces the average delay for data transmission by up to 20 percent.
Description:
Feature weighing methods are commonly used to find the relative significance among a set of features that are effectively used by the retrieval methods to search image sequences efficiently from large databases. As evidenced in the current literature, dynamic textures (image sequences with regular motion patterns) can be effectively modelled by a set of spatial and temporal motion distribution features like motion co-occurrence matrix. The aim of this paper is to develop effective feature weighting and retrieval methods for a set of dynamic textures while characterized by motion co-occurrence matrices.
Description:
Feature weighing methods are commonly used to find the relative significance among a set of features that are effectively used by the retrieval methods to search image sequences efficiently from large databases. As evidenced in the current literature, dynamic textures (image sequences with regular motion patterns) can be effectively modelled by a set of spatial and temporal motion distribution features like motion co-occurrence matrix. The aim of this paper is to develop effective feature weighting and retrieval methods for a set of dynamic textures while characterized by motion co-occurrence matrices.
Description:
Abstract— A block-based lossless video coding scheme using the notion of binning has been proposed in [1]. To further improve the compression and reduce the complexity, in this paper we investigate the impact of two sub-optimal motion search algorithms on the performance of this lattice-based scheme. While one of the algorithm tries avoiding motion vectors, the other tries to reduce complexity. Our experimental results have demonstrated that the loss due to sub-optimal motion search outweighs the gain when motion vectors are avoided. However, experimental results have shown that there is negligible performance loss when lowcomplexity sub-optimal three step search is used.
Description:
Modern surveillance systems are becoming highly automated in terms of scene understanding and event detection capabilities, and most existing methods rely on track-and motion-based features for event classification and anomaly detection. However, trajectory-based methods fail in public scenarios due to frequently loosing the object tracks, while the capabilities of motion-based methods are limited in detection of direction and velocity related anomalies. In this paper, a novel feature extraction and event detection method is presented without using any track and motion features where event discriminating characteristics are discovered from the dynamics of multiple temporal features extracted from foreground blobs and then confined in support vector machine based models for real-time event detection. Experimental results on benchmark datasets show that the proposed method can successfully discriminate panic-driven events like sudden split, runaway, and fighting from usual events.
Description:
Despite recent interests in developing vertical handoff decision algorithms, an essential component of the architecture of the next generation heterogeneous wireless networks, very few studies have so far reported any meaningful comparative performance analysis. This paper attempts to fill this gap in the literature by presenting a comprehensive study on the performance of three vertical handoff decision algorithms, namely, SAW (Simple Additive Weighting), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and MDP (Markov Decision Process). We have used both analytical and simulation tools (ns-2.29) to evaluate and compare expected total QoS offerings in the mean duration of a service under different state transition probability distributions, user perception models on the importance of QoS parameters, and network switching costs. To our surprise, we have observed TOPSIS achieving the best performance despite MDP's using the optimal policy. We suspect that the user satisfiability model used in MDP to estimate link rewards might have contradicted the underlying user perception model used to estimate normalised weight of each QoS parameter, which will be investigated in future.
Description:
Cognitive radio network (CRN) users are inherently expected to experience widely varied delays and jitters due to the uncertainty in channel availability. Supporting delay sensitive real-time services through CRNs thus remains a challenging task. This paper presents a novel technique to provision QoS guarantee in CRNs by modeling the resultant channel of multiple primary networks and finding the optimum number of primary channels to support a desired level of expected latency. In doing so, this paper introduces a cognitive radio based MAC, which can effectively co-exists with primary CSMA/CA networks by accurately estimating the start of the spectrum holes, reliably modeling channel occupation by the primary users, and using event-driven sensing to adaptively control the sensing frequency and interval. Simulation results with ns-2.33 reveal that a CR network based on the proposed MAC can achieve the targeted service delay time by appropriately selecting optimal WLAN primary channels.
Description:
Nighttime imagery poses significant challenges to its enhancement due to loss of color information and limitation of single sensor to capture complete visual information at night. To cope with this challenge, multiple sensors are used to capture reliable nighttime imagery which presents additional demands for reliable visual information fusion. In this paper, we present a system, Scarf, which proposes reliable image fusion using advanced feature extraction techniques and a novel semi-automatic colorization based on optimization conformal to human visual system. Subjective and objective quality evaluation proves the effectiveness of proposed system.
Description:
Among the existing block partitioning schemes, the pattern-based video coding (PVC) has already established its superiority at low bit-rate. Its innovative segmentation process with regular-shaped pattern templates is very fast as it avoids handling the exact shape of the moving objects. It also judiciously encodes the pattern-uncovered background segments capturing high level of interblock temporal redundancy without any motion compensation, which is favoured by the rate-distortion optimizer at low bit-rates. The existing PVC technique, however, uses a number of content-sensitive thresholds and thus setting them to any predefined values risks ignoring some of the macroblocks that would otherwise be encoded with patterns. Furthermore, occluded background can potentially degrade the performance of this technique. In this paper, a robust PVC scheme is proposed by removing all the content-sensitive thresholds, introducing a new similarity metric, considering multiple top-ranked patterns by the rate-distortion optimizer, and refining the Lagrangian multiplier of the H.264 standard for efficient embedding. A novel pattern-based residual encoding approach is also integrated to address the occlusion issue. Once embedded into the H.264 Baseline profile, the proposed PVC scheme improves the image quality perceptually significantly by at least 0.5 dB in low bit-rate video coding applications. A similar trend is observed for moderate to high bit-rate applications when the proposed scheme replaces the bi-directional predictive mode in the H.264 High profile.
Description:
Video Stabilization is now considered an old problem which is almost solved but there are still some connecting problems which needs research attention. One of such issues arises due to multiple unstable videos streams coming from multiple sensors which often contain complementary information. To enhance system performance, instability should be removed in a single go rather than stabilizing each sensor individually. This paper proposes a cooperative video stabilization framework, VSAMS for multisensory aerial data based on robust boosting curves which encapsulate stability of high spatial frequency information as used by flying parakeets (budgerigars). For reducing shake and jitter and preservation of actual camera path, a multistage smoothing approach is visualized. Experiments are performed on multisensory UAV data which contains infrared and electro-optical video streams. Subjective and objective quality evaluation proves effectiveness of the proposed cooperative stabilization framework.
Description:
Pattern-based video coding focusing on moving region in a macroblock has already established its superiority over recent H.264 video coding standard at very low bit rate. Obviously, a large number of pattern templates approximate the moving regions better however, after a certain limit no coding gain is observed due to the increase number of pattern identification bits. Recently, distributed video coding schemes used syndrome coding to predict the original information in decoder using side information. In this paper a novel pattern identification scheme is proposed which predicts the pattern from the syndrome codes and side information in decoder so that actual pattern identification number is not needed in the bitstream. The experimental results confirm that this new scheme successfully improves the rate-distortion performance compared to the existing pattern-based video coding as well as H.264 standard. This new scheme will also open another window of syndrome coding application.
Description:
Contention window based medium access protocols are of practical interest in low data rate wireless communication scenarios. In periodic data collection applications, nodes mostly produce small data packets that are collected by the cluster heads and routed to the base station. In this paper, a new mechanism for adaptively selecting the size of the contention window based on the number of contending nodes has been presented. The proposed scheme effectively reduces the number of collisions in periodic collection scenarios with fixed number of nodes. Theoretical analysis and simulation results demonstrate that, in periodic data collection processes, the new protocol reduces the data collection time significantly as compared to IEEE 802.11 and the recently proposed Synchronized Shared Contention Window (SSCW) based scheme.
Description:
Yang proposed the concept of borrow-and-return (BR) to leverage the unused server bandwidth when a group of popular videos being broadcast with the FSFC (first segment on the first channel) broadcasting schemes in order to improve the mean waiting time (MWT) of the viewers with the help of additional receiving bandwidth available at the high-end clients. The BR model borrows the bandwidth of the videos with no new-coming viewers during a timeslot to speed up the transmission of the first segments of some of the remaining videos. In this paper, we first address the relative advantage issue among various possible BR schemes by developing a parametric generic BR (GBR) scheme controlled externally by independent borrow parameters. Later, we propose a new BR (NBR) model by incorporating an efficient transmission strategy to reduce the MWT further. Finally, an optimal NBR scheme is developed by augmenting with the optimal borrow parameters, which significantly outperforms the existing and new BR schemes in terms of overall MWT.