Local spatial properties based image interpolation scheme using SVMs

Image interpolation plays an important role in image process applications. A novel support vector machines （SVMs） based interpolation scheme is proposed with increasing the local spatial properties in the source image as SVMs input patterns. After the proper neighbor pixels region is selected, trained support vectors are obtained by training SVMs with local spatial properties that include the average of the neighbor pixels gray values and the gray value variations between neighbor pixels in the selected region. The support vector regression machines are employed to estimate the gray values of unknown pixels with the neighbor pixels and local spatial properties information. Some interpolation experiments show that the proposed scheme is superior to the linear, cubic, neural network and other SVMs based interpolation approaches.

Spatial Asymptotic Properties of a System Wave Equations with Nonlinear Damping and Source Terms

In this paper,the wave equation defined in a semi-infinite cylinder is considered,in which the nonlinear damping and source terms is included.By setting an arbitrary parameter greater than zero in the energy expression,the fast growth rate or decay rate of the solution with spatial variables is obtained by using energy analysis method and differential inequality technique.Secondly,we obtain the asymptotic behavior of the solution on the external domain of the sphere.In addition,in this paper we also give some useful remarks which show that our results can be extended to more models.

A new measure for evaluating spatially related properties of traffic information credibility

With the wide applications of sensor network technology in traffic information acquisition systems,a new measure will be quite necessary to evaluate spatially related properties of traffic information credibility.The heterogeneity of spatial distribution of information credibility from sensor networks is analyzed and a new measure,information credibility function(ICF),is proposed to describe this heterogeneity.Three possible functional forms of sensor ICF and their corresponding expressions are presented.Then,two feasible operations of spatial superposition of sensor ICFs are discussed.Finally,a numerical example is introduced to show the calibration method of sensor ICF and obtain the spatially related properties of expressway in Beijing.The results show that the sensor ICF of expressway in Beijing possesses a negative exponent property.The traffic information is more abundant at or near the locations of sensor,while with the distance away from the sensor increasing,the traffic information credibility will be declined by an exponential trend.The new measure provides theoretical bases for the optimal locations of traffic sensor networks and the mechanism research of spatial distribution of traffic information credibility.

Study correlation vortices in the near-field of partially coherent vortex beams diffracted by an aperture

We have derived the analytical expression of the electric cross-spectral density in the near- field of partially coherent vortex beams diffracted by an aperture. Taking the Caussian Schell-model vortex beam as a typical example of partially coherent vortex beams, the spatial correlation properties and correlation vortices in the near-field of partially coherent vortex beams diffracted by a rectangle aperture are studied. It is shown that the off-axis displacement, spatial degree of coherence parameter, propagation distance, and the opening factor of the aperture affect the spectral degree of coherence and positions of correlation vortices. With the optimization algorithm, we obtain the symmetric distributing coherent vortex.

Image Segmentation via Mean Shift and Loopy Belief Propagation

This paper presents a novel approach that can quickly and effectively partition images based on fully exploiting the spatially coherent property. We propose an algorithm named iterative loopy belief propagation（iLBP） to integrate the homogenous regions and prove its convergence. The image is first segmented by mean shift（MS） algorithm to form over-segmented regions that preserve the desirable edges and spatially coherent parts. The segmented regions are then represented by region adjacent graph（RAG） . Motivated by k-means algorithm,the iLBP algorithm is applied to perform the minimization of the cost function to integrate the over-segmented parts to get the final segmentation result. The image clustering based on the segmented regions instead of the image pixels reduces the number of basic image entities and enhances the image segmentation quality. Comparing the segmentation result with some existing algorithms,the proposed algorithm shows a better performance based on the evaluation criteria of entropy especially on complex scene images.

Uncertainty propagation in dynamics of composite plates: A semi-analytical non-sampling-based approach

In this study,the influences of spatially varying stochastic properties on free vibration analysis of composite plates were investigated via development of a new approach named the deterministic-stochastic Galerkin-based semi-analytical method.The material properties including tensile modulus,shear modulus,and density of the plate were assumed to be spatially varying and uncertain.Gaussian fields with first-order Markov kernels were utilized to define the aforementioned material properties.The stochastic fields were decomposed via application of the K arhunen-Loeve theorem.A first-order shear deformation theory was assumed,following which the displacement field was defined using admissible trigonometric modes to derive the potential and kinetic energies.The stochastic equations of motion of the plate were obtained using the variational principle.The deterministic-stochastic Galerkin-based method was utilized to find the probability space of natural frequencies,and the corresponding mode shapes of the plate were determined using a polynomial chaos approach.The proposed method significantly reduced the size of the mathematical models of the structure,which is very useful for enhancing the computational efficiency of stochastic simulations.The methodology was verifed using a stochastic finite element method and the available results in literature.The sensitivity of natural frequencies and corresponding mode shapes due to the uncertainty of material properties was investigated,and the results indicated that the higher-order modes are more sensitive to uncertainty propagation in spatially varying properties.

Lau Effect Using LED Array for Lithography

Illumination with LEDs is of increasing interest in imaging and lithography.In particular,compared to lasers,LEDs are temporally and spatially incoherent,so that speckle effects can be avoided by the application of LEDs.Besides,LED arrays are qualified due to their high optical output power.However,LED arrays have not been widely used for investigating optical effects,e.g.,the Lau effect.In this paper,we propose the application of an LED array for realizing the Lau effect by taking into account the influence of the coherence properties of illumination on the Lau effect.Using spatially incoherent illumination with the LED array or a single LED,triangular distributed Lau fringes can be obtained.We apply the obtained Lau fringes in the optical lithography to produce analog structures.Compared to a single LED,the Lau fringes using the LED array have significantly higher intensities.Hence,the exposure time in the lithography process is largely reduced.