High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness by stack extension and rejects the information of ghost areas to avoid artifacts via fusion masks. Experiment results show that the proposed algorithm can remove ghost artifacts accurately for both static and handheld cameras, remain robust to scenes with complex motion and keep low complexity over recent advances including rank minimization based method and patch based method by 63.6% and 20.4% time savings averagely.

In this Letter, we investigate the outage performance of MIMO amplify-and-forward (AF) multihop relay networks with maximum ratio transmission/receiver antenna selection (MRT/RAS) over Nakagami-m fading channels in the presence of co-channel interference (CCI) or not. In particular, the lower bounds for the outage probability of MIMO AF multihop relay networks with/without CCI are derived, which provides an efficient means to evaluate the joint effects of key system parameters, such as the number of antennas, the interfering power, and the severity of channel fading. In addition, the asymptotic behavior of the outage probability is investigated, and the results reveal that the full diversity order can be achieved regardless of CCI. In addition, simulation results are provided to show the correctness of our derived analytical results.

We consider a physical-layer network coding (PNC) scheme based on M-ary continuous phase frequency shift keying (M-CPFSK) modulation for a bidirectional relay network. In this scheme, the maximum-likelihood sequence detection (MLSD) algorithm for the relay receiver over Rayleigh fading channels is discussed. Moreover, an upper bound on the minimum Euclidean distance for the superimposed signals is analyzed and the corresponding lower bound for the average symbol error rate (SER) at the relay is derived. Numerical results are also sustained by simulations which corroborate the exactness of the theoretical analysis.

The Virtual Software Token Protocol was proposed by Know as a practical method for secure public key infrastructure roaming. However, he recently found a weakness of the protocol under the original assumption, and proposed two revised versions, namely refinement and improvement, which lost the desirable properties of scalability and efficiency respectively. In this letter, a secure improvement is proposed for better performance in both scalability and efficiency. Unlike the author's improvement, our improvement provides parallel execution as the original protocol did.

In 2002, Zhu et al. proposed a password authenticated key exchange protocol based on RSA such that it is efficient enough to be implemented on most of the target low-power devices such as smart cards and low-power Personal Digital Assistants in imbalanced wireless networks. Recently, YEH et al. claimed that Zhu et al.'s protocol not only is insecure against undetectable on-line password guessing attack but also does not achieve explicit key authentication. Thus they presented an improved version. Unfortunately, we find that YEH et al.'s password guessing attack does not come into existence, and that their improved protocol is vulnerable to off-line dictionary attacks. In this paper we describe our observation in details, and also comment for the original protocol on how to achieve explicit key authentication as well as resist against other existent attacks.

Adaptation process of retina helps human visual system to see a high dynamic range scene in real world. This paper presents a simple static local adaptation method for high dynamic range image compression based on a retinal model. The proposed simple model aims at recreating the same sensations between the real scene and the range compressed image on display device when viewed after reaching steady state local adaptation respectively. Our new model takes the display adaptation into account in relation to the scene adaptation based on the retinal model. In computing local adaptation, the use of nonlinear edge preserving bilateral filter presents a better tonal rendition in preserving the local contrast and details while avoiding banding artifacts normally seen in local methods. Finally, we demonstrate the effectiveness of the proposed model by estimating the color difference between the recreated image and the target visual image obtained by trial and error method.

Driver fatigue detection has become crucial in vehicle safety technology. Achieving high accuracy and real-time performance in detecting driver fatigue is paramount. In this paper, we propose a novel driver fatigue detection algorithm based on dynamic tracking of Facial Eyes and Yawning using YOLOv7, named FEY-YOLOv7. The Coordinate Attention module is inserted into YOLOv7 to enhance its dynamic tracking accuracy by focusing on coordinate information. Additionally, a small target detection head is incorporated into the network architecture to promote the feature extraction ability of small facial targets such as eyes and mouth. In terms of compution, the YOLOv7 network architecture is significantly simplified to achieve high detection speed. Using the proposed PERYAWN algorithm, driver status is labeled and detected by four classes: open_eye, closed_eye, open_mouth, and closed_mouth. Furthermore, the Guided Image Filtering algorithm is employed to enhance image details. The proposed FEY-YOLOv7 is trained and validated on RGB-infrared datasets. The results show that FEY-YOLOv7 has achieved mAP of 0.983 and FPS of 101. This indicates that FEY-YOLOv7 is superior to state-of-the-art methods in accuracy and speed, providing an effective and practical solution for image-based driver fatigue detection.

For an [n, k, d] (r, δ)-locally repairable codes ((r, δ)-LRCs), its minimum distance d satisfies the Singleton-like bound. The construction of optimal (r, δ)-LRC, attaining this Singleton-like bound, is an important research problem in recent years for thier applications in distributed storage systems. In this letter, we use Reed-Solomon codes to construct two classes of optimal (r, δ)-LRCs. The optimal LRCs are given by the evaluations of multiple polynomials of degree at most r - 1 at some points in Fq. The first class gives the [(r + δ - 1)t, rt - s, δ + s] optimal (r, δ)-LRC over Fq provided that r + δ + s - 1≤q, s≤δ, s

A fuzzy-like phenomenon is observed in a chaotic neural network operating as dynamic autoassociative memory. When an external stimulation with properties shared by two stored patterns is applied to the chaotic neural network, the output of the network transits between the two patterns. The ratio of the network visiting two stored patterns is dependent on the ratio of the Hamming distances between the external stimulation and the two stored patterns. This phenomenon is similar to the human decision-making process, which can be described by fuzzy set theory. Here, we analyze the fuzzy-like phenomenon from the viewpoint of the fuzzy set theory.

Detecting key frames in videos has garnered substantial attention in recent years, it is a point-level task and has deep research value and application prospect in daily life. For instances, video surveillance system, video cover generation and highlight moment flashback all demands the technique of key frame detection. However, the task is beset by challenges such as the sparsity of key frame instances, imbalances between target frames and background frames, and the absence of post-processing method. In response to these problems, we introduce a novel and effective Temporal Interval Guided (TIG) framework to precisely localize specific frames. The framework is incorporated with a proposed Point-Level-Soft non-maximum suppression (PLS-NMS) post-processing algorithm which is suitable for point-level task, facilitated by the well-designed confidence score decay function. Furthermore, we propose a TIG-loss, exhibiting sensitivity to temporal interval from target frame, to optimize the two-stage framework. The proposed method can be broadly applied to key frame detection in video understanding, including action start detection and static video summarization. Extensive experimentation validates the efficacy of our approach on action start detection benchmark datasets: THUMOS’14 and Activitynet v1.3, and we have reached state-of-the-art performance. Competitive results are also demonstrated on SumMe and TVSum datasets for deep learning based static video summarization.

In this paper, we investigate a cooperative communication system comprised of a source, a destination, and multiple decode-and-forward (DF) relays in the presence of a potential malicious eavesdropper is within or without the coverage area of the source. Based on the more general Nakagami-m fading channels, we analyze the security performance of the single-relay selection and multi-relay selection schemes for protecting the source against eavesdropping. In the single-relay selection scheme, only the best relay is chosen to assist in the source transmission. Differing from the single-relay selection, multi-relay selection scheme allows multiple relays to forward the source to the destination. We also consider the classic direct transmission as a benchmark scheme to compare with the two relay selection schemes. We derive the exact closed-form expressions of outage probability (OP) and intercept probability (IP) for the direct transmission, the single-relay selection as well as the multi-relay selection scheme over Nakagami-m fading channel when the eavesdropper is within and without the coverage area of the source. Moreover, the security-reliability tradeoff (SRT) of these three schemes are also analyzed. It is verified that the SRT of the multi-relay selection consistently outperforms the single-relay selection, which of both the single-relay and multi-relay selection schemes outperform the direct transmission when the number of relays is large, no matter the eavesdropper is within or without the coverage of the source. In addition, as the number of DF relays increases, the SRT of relay selection schemes improve notably. However, the SRT of both two relay selection approaches become worse when the eavesdropper is within the coverage area of the source.

A fuzzy-like phenomenon in a dynamic neural network is demonstrated and analyzed. The network operates as a dynamic associative memory. Each neuron of the dynamic neural network has an all-or-none output and exponentially decaying refractoriness. When several related patterns are stored in the dynamic neural network and an external stimulus with a property shared by two of the stored patterns is applied to the neural network, the output of the neural network dynamically transits between the two stored patterns. The frequency ratio that the network visits the two stored patterns is dependent on the ratio of the Hamming distances between the external pattern and the two stored patterns. This phenomenon is similar to the human decision-making process, some of which characteristics can be described by fuzzy set theory. A framework for the analysis of this phenomenon is proposed, and is used to derive sufficient conditions which ensure the dynamical transition between the two stored patterns. The properties of the transition in the network are also discussed.

Solution space smoothing allows a local search heuristic to escape from a poor, local minimum. In this paper, we propose a technique that can smooth the rugged terrain surface of the solution space of a placement problem. We test the smoothing heuristics for MCNC benchmarks, and for VLSI placement with pre-placed modules and placement with consideration of congestion. Experiment results demonstrated that solution space smoothing is very efficient for VLSI module placement, and it can be applied to all floorplanning representations proposed so far.

A novel distributed ranging method for wireless sensor networks (WSN) is proposed in this letter. Linear frequency modulation (LFM) waves are emitted from the two antenna elements equipped at the anchor node simultaneously to create an interference field. Through the frequency measurement of local RSSI (Received Signal Strength Indication) signal, the horizontal distance from the anchor node can be estimated independently at each sensor. Analysis and simulation results demonstrate the effectiveness of our proposed method.

In this letter, we propose a simple distributed space-frequency code with both timing errors and multiple carrier frequency offsets (CFO) in asynchronous cooperative communications. By employing both the Alamouti coding approach and the transmit repetition diversity technique, full diversity gain can be achieved by the fast symbol-wise maximum likelihood (ML) decoding at the destination node. Analysis and simulations demonstrate the effectiveness of the proposed method.

Although the classical vector median filter (VMF) has been widely used to suppress the impulse noise in the color image, many thin color curve pixels aligned in arbitrary directions are usually removed out as impulse noise. This serious problem can be solved by the proposed method that can protect the thin curves in arbitrary direction in color image and remove out the impulse noise at the same time. Firstly, samples in the 3x3 filter window are considered to preliminarily detect whether the center pixel is corrupted by impulse noise or not. Then, samples outside a 5x5 filter window are conditionally and partly considered to accurately distinguish the impulse noise and the noise-free pixel. At last, based on the previous outputs, samples on the processed positions in a 3x3 filter window are chosen as the samples of VMF operation to suppress the impulse noise. Extensive experimental results indicate that the proposed algorithm can be used to remove the impulse noise of color image while protecting the thin curves in arbitrary directions.

Rapid building damage identification plays a vital role in rescue operations when disasters strike, especially when rescue resources are limited. In the past years, supervised machine learning has made considerable progress in building damage identification. However, the usage of supervised machine learning remains challenging due to the following facts: 1) the massive samples from the current damage imagery are difficult to be labeled and thus cannot satisfy the training requirement of deep learning, and 2) the similarity between partially damaged and undamaged buildings is high, hindering accurate classification. Leveraging the abundant samples of auxiliary domains, domain adaptation aims to transfer a classifier trained by historical damage imagery to the current task. However, traditional domain adaptation approaches do not fully consider the category-specific information during feature adaptation, which might cause negative transfer. To address this issue, we propose a novel domain adaptation framework that individually aligns each category of the target domain to that of the source domain. Our method combines the variational autoencoder (VAE) and the Gaussian mixture model (GMM). First, the GMM is established to characterize the distribution of the source domain. Then, the VAE is constructed to extract the feature of the target domain. Finally, the Kullback-Leibler (KL) divergence is minimized to force the feature of the target domain to observe the GMM of the source domain. Two damage detection tasks using post-earthquake and post-hurricane imageries are utilized to verify the effectiveness of our method. Experiments show that the proposed method obtains improvements of 4.4% and 9.5%, respectively, compared with the conventional method.

In this paper, we explore how to enhance the physical layer security performance in downlink cellular networks through cooperative jamming technology. Idle user equipments (UE) are used to cooperatively transmit jamming signal to confuse eavesdroppers (Eve). We propose a threshold-based jammer selection scheme to decide which idle UE should participate in the transmission of jamming signal. Threshold conditions are carefully designed to decrease interference to legitimate channel, while maintain the interference to the Eves. Moreover, fewer UE are activated, which is helpful for saving energy consumptions of cooperative UEs. Analytical expressions of the connection and secrecy performances are derived, which are validated through Monte Carlo simulations. Theoretical and simulation results reveal that our proposed scheme can improve connection performance, while approaches the secrecy performance of [12]. Furthermore, only 43% idle UEs of [12] are used for cooperative jamming, which helps to decrease energy consumption of network.

In this paper, the average symbol error probability (SEP) performance of decode-and-forward (DF) relaying mobile-to-mobile (M2M) systems with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated. The moment generating function (MGF) method is used to derive exact SEP expressions, and the analysis is verified via simulation. The optimal power allocation problem is investigated. Performance results are presented which show that the fading coefficient, number of cascaded components, relative geometrical gain, number of antennas, and power allocation parameter have a significant effect on the SEP.

Because solar energy is intermittent and a ship's power-system load fluctuates and changes abruptly, in this work, the solar radiation parameters were adjusted according to the latitude and longitude of the ship and the change of the sea environment. An objective function was constructed that accounted for the cost and service life simultaneously to optimize the configuration of the marine diesel engine hybrid energy system. Finally, the improved artificial bee colony algorithm was used to optimize and obtain the optimal system configuration. The feasibility of the method was verified by ship navigation tests. This method exhibited better configuration performance optimization than the traditional methods.