The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Classification of SAR images is a challenging task as the radiometric properties of a class may not be constant throughout the image. The assumption made in most classification algorithms that a class can be modeled by constant parameters is then not valid. In this paper, we propose a classification algorithm based on two Markov random fields that accounts for local and global variations of the parameters...
To explore the capability of quad polarimetric SAR images from a new pursuit monostatic mode of TerraSAR-X and TanDEM-X, a novel process chain for ship detection and velocity estimation is proposed in this paper. Compared with the classic processing chain used for single SAR image, more efficient techniques are integrated into this novel chain, which take advantage of the new image mode and its excellent...
Sparse unmixing of hyperspectral data is an important technique which aims at estimating the fractional abundances of endmembers (pure spectral components). It is well known that enforcing sparseness becomes a necessary process in sparse unmixing methods. To better exploit the sparsity in hyperspectral imagery, a double reweighted sparse unmixing algorithm has been proposed. However, it focusses on...
Hyperspectral sensors provides informative data in many fields related to Earth observation. On the coastal zone, the inversion of radiative transfer models of the light has shown the ability to estimate parameters characterizing the water column. Particularly the water column depth, its concentration in non-algal particles, in phytoplankton, the bottom reflectance can be retrieved. Nevertheless the...
The synergistic analysis of light detection and ranging (LiDAR) and hyperspectral data is attracting a significant interest in recent years due to the complementary nature of these two sources of remote sensing data. In this paper, we propose a new spectral-spatial classification method able to jointly exploit these two kinds of data. Our work is based on three innovative components: 1) a superpixel...
Traditional particle swarm optimization(PSO) will be failed because of falling into local optimum solutions and converging too slowly when being used to optimize planar array pattern. So a new method is presented to improve the traditional PSO convergence by means of efficient estimation of the optimum particle's initial values. A desired pattern is first constructed, and then the corresponding aperture...
Media playout buffer is widely employed by today's streaming media player to cope with short-term network variation and achieve continuous playout. However, the playout buffer inevitably introduces additional latency, affecting mobile live streaming experience. In this paper, we propose a novel adaptive playout buffer management approach to dynamically optimize the buffer latency while to a great...
Single-image blind deblurring could be considered as an important preprocessing step in imaging information fusion. Its purpose is to simultaneously estimate blur kernel and latent sharp image from only one observed blurred image. Blind deblurring has been attracting increasing attention in the fields of image processing, computer vision, computational photography, etc. However, it is a typically...
Analogy-based software effort estimation is a method to estimate the project cost of an unseen project based on analogies against previous projects sharing selected features. The validity of the selected features depends on many factors, and one of most crucial factors is the effectiveness of the datapreprocessing techniques applied to the datasets of the previous projects. In this paper, we report...
This paper addresses the problem of joint detection and estimation fusion when sensor quantized data are correlated in the distributed system. The traditional methods to handle this joint problem tend to treat the detection and estimation tasks separately, which put more emphasis on the detection part but treat the estimation part sub-optimally. In this work, the joint detection and estimation fusion...
This paper proposes a new approach for constrained multiple model (MM) maximum a posteriori (MAP) estimation through the expectation-maximization (EM) method by using our previously developed constrained sequential list Viterbi algorithm (CSLVA). The approach is general and applicable for any type of constraints provided they are verifiable. Specific algorithms for implementation are designed, and...
The average time a resource needs to process incoming requests in a monitored workload mix is a key parameter of stochastic performance models. Direct measurement of these resource demands is usually infeasible due to instrumentation overheads causing measurement interferences and perturbation in production environments.Thus, a number of statistical estimation approaches (e.g., based on optimization,...
For a discrete-time linear system that has an open-loop pole outside the unit circle and is subject to actuator saturation, global asymptotic stabilization cannot be achieved. As a consequence, a discrete-time multi-agent system containing such an actuator saturating agent can only reach regional consensus, that is, the consensus can be achieved only if the initial state of each agent resides in a...
This paper presents three iterative methods for orientation estimation. The first two are based on iterated Extended Kalman filter (IEKF) formulations with different state representations. The first is using the well-known unit quaternion as state (q-IEKF) while the other is using orientation deviation which we call IMEKF. The third method is based on nonlinear least squares (NLS) estimation of the...
This paper presents a new depth estimation method for multiview systems with arbitrary camera locations. The method exploits the graph cuts method, where vertices of the graph represent segments used for controlling the trade-off between the quality of depth maps and the time of estimation, while preserving the original resolution of a depth map. Moreover, the inter-view consistency of the depth maps,...
Noise estimation is crucial in many image processing algorithms such as image denoising. Conventionally, the noise is assumed as signal-independent additive white Gaussian process. However, for the real raw-data of imaging sensors, the present noise is better modeled as signal-dependent noise. In this work, we propose an efficient image sensor noise estimation method based on iterative re-weighted...
In this paper, sparsity-promoting sensor selection algorithms for target tracking with quantized data are developed. We formulate sensor selection as an optimization problem that aims to strike a balance between estimation accuracy and the number of selected sensors. To cope with sensor selection problems in large-scale wireless sensor networks (WSNs), we propose a fast centralized optimization algorithm...
Distributed algorithms are proposed to solve distributed optimization problems for a network of strongly connected agents in this paper. The proposed algorithms are based on a combination of a leader-following consensus protocol and the gradient descent method/primal-dual dynamics. In the leader-following consensus protocol, each agent acts as a virtual leader that provides its local measurements...
This paper deals with the stability regions for continuous-time systems with actuator saturation via homogeneous parameter-dependent quadratic Lyapunov functions(HPD-QLF). Using the homogeneous parameter-dependent quadratic Lyapunov functions, a new method about estimation of stability regions is obtained. Through formulating the problem as LMIs optimization problem, the new method can get less conservative...
This paper deals with the real-time steady-state optimization of slow dynamic processes under plant-model mismatch. A novel scheme that iteratively adapts the process set-points (or operating parameters) to attain an economic optimum is proposed. Based on computing the next steady state from the process transient response to the current set-point change, this scheme can significantly reduce the time...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.