Variational Image Segmentation with Constraints

The research of Huizhu Pan addresses the problem of image segmentation with constraints though designing and solving various variational models. A novel constraint term is designed for the use of landmarks in image segmentation. Two region-based segmentation models were proposed where the segmentation contour passes through landmark points. A more stable and memory efficient solution to the self-repelling snakes model, a variational model with the topology preservation constraint, was also designed

Effect of Mytilus coruscus selective filtration on phytoplankton assemblages

The feeding selectivity of bivalves can play an important role in shaping the structure of phytoplankton communities of natural waters. This could be particularly true in waters with intensive bivalves farming, like Sungo Bay, Northern China. Understanding the role of bivalve feeding behavior is important for assessing how the dense cultivation of bivalves may affect phytoplankton community composition and food web structure in farm areas. In this study, we investigated the feeding selectivity of blue mussel Mytilus coruscus on natural phytoplankton assemblages in Sungo Bay using both optical microscopy and HPLC-pigment analysis. Results showed that cryptophytes dominated the phytoplankton community and made up 66.1% of the total phytoplankton abundance. A comparison of phytoplankton composition between natural and filtered seawater showed that M. coruscus preferred cryptophytes and dinoflagellates than Chaetoceros spp. and Skeletonema spp. Cryptophytes were not detected in gut contents by microscopic observation, while their marker pigment alloxanthin was present, suggesting they were also consumed by M. coruscus and can be readily digested. This highlights the shortcomings of microscopic methods and the significance of HPLC-pigment analysis in obtaining a comprehensive understanding of feeding selectivity of bivalves. The proportions of Chaetoceros spp. and Skeletonema spp. in gut contents were significantly lower than their proportions in the seawater, and contrastingly, the proportions of Cocconeis spp. and Pinnularia spp. showed opposite patterns. The marker pigments prasinoxanthin and zeaxanthin were detected in the gut of M. coruscus indicating that picophytoplankton (e.g., prasinophytes and Synechococcus) are also food sources for this bivalve. This information furthers our understanding of bivalve aquaculture and environment interactions.publishedVersio

The Chan-Vese Model With Elastica and Landmark Constraints for Image Segmentation

In order to completely separate objects with large sections of occluded boundaries in an image, we devise a new variational level set model for image segmentation combining the Chan-Vese model with elastica and landmark constraints. For computational efficiency, we design its Augmented Lagrangian Method (ALM) or Alternating Direction Method of Multiplier (ADMM) method by introducing some auxiliary variables, Lagrange multipliers, and penalty parameters. In each loop of alternating iterative optimization, the sub-problems of minimization can be easily solved via the Gauss-Seidel iterative method and generalized soft thresholding formulas with projection, respectively. Numerical experiments show that the proposed model can not only recover larger broken boundaries but can also improve segmentation efficiency, as well as decrease the dependence of segmentation on parameter tuning and initialization

Secrecy Capacity Maximization of UAV-Enabled Relaying Systems with 3D Trajectory Design and Resource Allocation

Unmanned aerial vehicles (UAVs) have attracted considerable attention, thanks to their high flexibility, on-demand deployment and the freedom in trajectory design. The communication channel quality can be effectively improved by using UAV to build a line-of-sight communication link between the transmitter and the receiver. Furthermore, there is increasing demand for communication security improvement, as the openness of a wireless channel brings serious threat. This paper formulates a secrecy capacity optimization problem of a UAV-enabled relay communication system in the presence of malicious eavesdroppers, in which the secrecy capacity is maximized by jointly optimizing the UAV relay’s location, power allocation, and bandwidth allocation under the communication quality and information causality constraints. A successive convex approximation–alternative iterative optimization (SCA-AIO) algorithm is proposed to solve this highly coupled nonconvex problem. Simulation results demonstrate the superiority of the proposed secrecy transmission strategy with optimal trajectory design and resource allocation compared with the benchmark schemes and reveal the impacts of communication resources on system performance

Energy-Spectrum Efficiency Trade-Off in UAV-Enabled Mobile Relaying System with Bisection-PSO Algorithm

Unmanned aerial vehicle (UAV)-enabled mobile relaying is regarded as an important wireless connectivity component in areas without infrastructure coverage due to its rapid response, strong mobility, and low cost. This paper studies a delay tolerant UAV-enabled mobile relaying system and adopts the load-carry-and-deliver paradigm. The UAV is employed to assist in the information transmission from a ground transmitter to a ground receiver with their direct link blocked. Two kinds of UAV flight trajectories are proposed in this system, i.e., a straight line and circular trajectory. Suppose that the UAV employs time-division duplexing (TDD)-based decode-and-forward (DF) relaying. This paper then aims to maximize the spectrum efficiency (SE) and energy efficiency (EE) in of the UAV-enabled relaying system by jointly optimizing the time allocation, flight speed, and the flying radius of the circular trajectory. Then, we develop an efficient algorithm by leveraging the bisection method and particle swarm optimization (PSO) algorithm. Simulation results show the superiority of the proposed algorithm as compared to other benchmark schemes. In addition, numerical results show that, when the communication distance is 1000 m, the SE and EE performance of the circular trajectory is better than the SLF trajectory when the obstacle height is greater than 300 m. Thus, the height of the obstacle between the communication nodes and the trade-off between the SE and EE should be taken into account when we design the optimal trajectory of the UAV-enabled mobile relaying system

Energy-Spectrum Efficiency Trade-Off in UAV-Enabled Mobile Relaying System with Bisection-PSO Algorithm

Unmanned aerial vehicle (UAV)-enabled mobile relaying is regarded as an important wireless connectivity component in areas without infrastructure coverage due to its rapid response, strong mobility, and low cost. This paper studies a delay tolerant UAV-enabled mobile relaying system and adopts the load-carry-and-deliver paradigm. The UAV is employed to assist in the information transmission from a ground transmitter to a ground receiver with their direct link blocked. Two kinds of UAV flight trajectories are proposed in this system, i.e., a straight line and circular trajectory. Suppose that the UAV employs time-division duplexing (TDD)-based decode-and-forward (DF) relaying. This paper then aims to maximize the spectrum efficiency (SE) and energy efficiency (EE) in of the UAV-enabled relaying system by jointly optimizing the time allocation, flight speed, and the flying radius of the circular trajectory. Then, we develop an efficient algorithm by leveraging the bisection method and particle swarm optimization (PSO) algorithm. Simulation results show the superiority of the proposed algorithm as compared to other benchmark schemes. In addition, numerical results show that, when the communication distance is 1000 m, the SE and EE performance of the circular trajectory is better than the SLF trajectory when the obstacle height is greater than 300 m. Thus, the height of the obstacle between the communication nodes and the trade-off between the SE and EE should be taken into account when we design the optimal trajectory of the UAV-enabled mobile relaying system

Inter-dependent rate-distortion modeling for video coding and its application to rate control

Rate control scheme using independent rate-distortion (R-D) model at the minimum coding unit (macroblock) level has been widely discussed in the literature where R-D optimization is performed without consideration of the inter-dependencies of different coding units. In this paper, we extend these techniques to the more general situations - rate control for inter-dependent video coding units. The inter-dependent distortion-quantization (D-Q) model and ratequantization (R-Q) model are formulated separately based on the analysis of the relationship between the spatial-domain residual and the transform-domain residual. Then a window-based rate control scheme with frame bit allocation and video quality optimization is proposed, which uses the approximated R-D model to reduce the computational complexity. Simulation results demonstrate that the proposed algorithm shows excellent peak signal-to-noise ratio (PSNR) performance under the bit rate constraint. This one-pass rate control scheme is highly practical for the real-time video coding application.EICPCI-S(ISTP)[email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected]

Variational total curvature model for multiplicative noise removal

The multiplicative noise removal problem has received considerable attention recently. To solve this problem, various variational models have been proposed, which minimise an energy functional composed of the data term and the regularisation term. Regarding the regularisation term, a first‐order model is frequently used to remove multiplicative noise, which may cause staircase effect and loss of contrast in the output image. In this study, the authors use a second‐order model, the total curvature (TC), to solve the above problem. The TC model has the benefit of removing the staircase effect and maintaining image edges, contrasts and corners. The augmented Lagrange method is utilised to solve the proposed TC model by introducing auxiliary variables, Lagrange multipliers and using alternating optimisation strategy. In each loop of optimisation, the fast Fourier transform, generalised soft threshold formulas, projection method and gradient descent method are integrated effectively. The experimental results show that the TC model can effectively remove staircase effect and preserve smoothness, via comparison with the first‐order model (total variation regularisation and Perona–Malik regularisation). Furthermore, the TC model is better than another second‐order model based on bounded Hessian regularisation in preserving contrast and corner