The specular component of light scattering and the charac- terization of the height distribution for random surfaces

The relations between the specular reflection component of the intensity scattered by random surfaces and the height distributions of the surfaces are analyzed theoretically. In the extraction of the height distribution, both the phase and the amplitude of the specular wave are required. The measured specular intensity data versus the perpendicular component of the wave vector are used for the retrieval of the phase distribution of the specular wave, in which the Ger-chberg-Saxton iterative algorithm is employed, and the characterization of the height distribution of random surfaces is accomplished. In the experiment, two samples with Gaussian and quasi-two level height distributions, respectively, are practically measured and the results of the height probability density function obtained by light scattering method are in good accordance with those by atomic force microscopy. The method of this paper is of important significance for the characterizations and studies of random surfaces.     

The autocorrelation of speckles in deep Fresnel diffraction region and characterizations of random self-affine fractal surfaces

This paper studies the correlation properties of the speckles in the deep Fresnel diffraction region produced by the scattering of rough self-affine fractal surfaces. The autocorrelation function of the speckle intensities is formulated by the combination of the light scattering theory of Kirchhoff approximation and the principles of speckle statistics. We propose a method for extracting the three surface parameters, i.e. the roughness w, the lateral correlation length ξ and the roughness exponent α, from the autocorrelation functions of speckles. This method is verified by simulating the speckle intensities and calculating the speckle autocorrelation function. We also find the phenomenon that for rough surfaces with α= 1, the structure of the speckles resembles that of the surface heights, which results from the effect of the peak and the valley parts of the surface, acting as micro-lenses converging and diverging the light waves.     

Measurements of femtosecond temporal speckle field of a random medium

The femtosecond temporal speckle field of a random medium is studied theoretically and experimentally. Femtosecond temporal speckle arises from the interference of multiple randomly scattered electric fields. The femtosecond temporal speckle field is measured with a cross-correlation frequency-resolved optical gating method. The spatial average of the speckle field yields a smooth transmitted profile. The speckle field is a circular complex Gaussian variable because the scattered light beams from different trajectories have no correlation with each other. The field and the intensity profiles of individual speckle spots fluctuate randomly in time. The ensemble average of the temporal intensity profiles converges, thereby yielding the photon travel time probability distribution function.     

Speckle noise reduction in digital holography with spatial light modulator and nonlocal means algorithm

An integrated method based on optical and digital image processing is presented to suppress speckle in digital holography. A spatial light modulator is adopted to introduce random phases to the illuminating beam. Multiple holograms are reconstructed and superimposed, and the intensity is averaged to smooth the noise. The adaptive algorithm based on the nonlocal means is designed to further suppress the speckle. The presented method is compared with other methods reduction is improved, and the proposed method is effective The experimental results show that speckle and feasible.     

Speckle reduction algorithm for laser underwater image based on curvelet transform

Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information.     

Speckle reduction algorithm for laser underwater image based on curvelet transform

Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information.     

Measurement of Random Surface Parameters of Weak Scatterers using the Speckle Contrast Method

Theoretical analysis shows that the deviation roughness ωand the lateral correlation length ξ of a weak scattering object determine the different properties of the contrast of the speckles in the image plane of a 4f system.Experimentally,we have measured the data of the speckle contrast versus the radius R of the variable filtering aperture.By fitting the theoretical results to these data,we extract the parameters ω and ξ of the random surfaces with Gaussian correlation.This method can determine the two parameters simultaneously and independently,and pre-calibrations are not needed.     

Variational denoising method for electronic speckle pattern interferometry

Traditional speckle fringe patterns by electronic speckle pattern interferometry(ESPI)are inherently noisy and of limited visibility,so denoising is the key problem in ESPI.We present the variational denoising method for ESPI.This method transforms the image denosing to minimizing an appropriate penalized energy function and solving a partial differential equation.We test the proposed method on computer- simulated and experimental speckle correlation fringes,respectively.The results show that this technique is capable of significantly improving the quality of fringe patterns.It works well as a pre-processing for the fringe patterns by ESPI.     

Intensity Correlation Function of Light Scattering from a Weakly One-Dimensional Random Rough Surface

Based on the Kirchhoff approximation and Gaussian moment theorem, we present a general expression of the intensity correlation scattered from a weakly one-dimensional rough surface, which is applicable to the cases by either two different wavelengths or two different angles of incidence. By using a Gaussian surface model, we give the numerical results for the intensity correlation function with two different wavelengths specially. The results show that with the increasing surface roughness and the decreasing surface correlation length, the correlation function decreases in specular direction and increases in other directions, which indicates that the study of the correlation of the intensities is helpful when investigating the statistical parameters of rough objects. Also the results show that the increase of rms roughness can result in the narrower correlation bandwidth.     

A modified image enhancement algorithm based on color constancy

According to the color constancy theory, a modified variation Retinex is proposed for improving the visibility of the dark regions in images under insufficient and/or non-uniform lighting conditions. A new penalty functional based on nonlinear diffusion and correlation between the reflectance and the given image is designed for the intensity image enhancement, followed by adaptive color compensation. With high computational efficiency achieved by an improved multi-resolution algorithm, simulation results prove that the proposed method shows more colorful and vivid visual performance, and achieves wider dynamic range with higher objective standard values.     

Research on synthetic aperture radar imaging technology of one-dimensional layered rough surfaces

A quick and exact imaging method for one-dimensional layered rough surfaces is proposed in this paper to study the scattering characteristics of a layered medium that exists widely in nature.The boundary integral equations of layered rough surfaces are solved by using the propagation-inside-layer expansion combined with the forward and backward spectral acceleration method(PILE+FB-SA),and the back scattering data are obtained.Then,a conventional synthetic aperture radar(SAR) imaging procedure called back projection method is used to generate a two-dimensional(2D) image of the layered rough surfaces.Combined with the relative dielectric permittivity of realistic soil,the random rough surfaces with Gauss spectrum are used to simulate the layered medium with rough interfaces.Since the back scattering data are computed by using the fast numerical method,this method can be used to study layered rough surfaces with any parameter,which has a great application value in the detection and remote sensing areas.     

Properties of Speckle Intensities in Near-Field Optical Regions by Numerical Solutions of Wave Equations

Starting from the electromagnetic wave equations and boundary conditions and using Green‘s integral theorem,we implement the rigorous numerical solutions of the speckle field produced by scattering of dielectric randomsurfaces in the optical near-field. The average sizes of speckle granules are enlarged very quickly with the increaseof the distance in the range less than a wavelength. It is found that the speckle contrast in the near-field and inthe neighbourhood region is inversely proportional to the square of lateral correlation length at its large valuesand linearly decreases with the roughness exponent.     

New color correction method for multi-view video using disparity vector information

Color inconsistency is an urgent problem to be solved in free viewpoint television.In this letter,a new color correction method is proposed by using disparity vector information.At first,we separate foreground and background from the scene with a method of mean-removed disparity estimation.Then the correction parameters are estimated by adopting linear fitting for foreground and background regions,respectively. Next,with expectation-maximization algorithm,we integrate correction parameters of foreground and background to get the final corrected image.Finally,video tracking technique is performed to correct multi-view video.Experimental results show that the proposed method is quite effective.     

Semi-blind image restoration based on Chan-Vese denoising model

A semi-blind image restoration algorithm is proposed based on reduced non-convex approximation of Luminita Vese and Tony Chan's(C-V)denoising model.Compared with C-V denoising model,we modify the fidelity term and add a term on point spread function(PSF).The function depends on two variables: the image function to be restored u and the standard deviation of Gaussian kernel to be estimatedσ. Then the problems consist in solving a system with two coupled equations.Compared with the Leah Bar's semi-blind image restoration model which must solve three coupled equations,our method only needs to solve two equations.Furthermore,the estimation of f by our algorithm is superior to Leah Bar's algorithm. The experimental results demonstrate that the proposed method is effective.     

A polynomial hybrid reflection model and measurement of its parameters based on images of sample

Reflectance model is a basic concept in computer vision.Some existing models combining the classical diffuse reflectance model and those for surfaces containing specular components can approximately describe real reflectance.But the ratio of diffuse and specular reflection decided manually has no clear meaning. We propose a new polynomial hybrid reflectance model.The reflectance map equation with a known shape (for example cylinder)as a sample is used to estimate parameters of the proposed reflectance model by least square regression algorithm.Then the reflectance parameters for surfaces of the same class of materials can be determined.Experiments are performed for a metal surface.The synthesis images produced by the proposed method and existing ones are compared with the real acquired image,and the results show that the proposed reflectance model is suitable for describing real reflectance.     

A modified fractional least mean square algorithm for chaotic and nonstationary time series prediction

A method of modifying the architecture of fractional least mean square （FLMS） algorithm is presented to work with nonlinear time series prediction. Here we incorporate an adjustable gain parameter in the weight adaptation equation of the original FLMS algorithm and absorb the gamma function in the fractional step size parameter. This approach provides an interesting achievement in the performance of the filter in terms of handling the nonlinear problems with less computational burden by avoiding the evaluation of complex gamma function. We call this new algorithm as the modified fractional least mean square （MFLMS） algorithm. The predictive performance for the nonlinear Mackey glass chaotic time series is observed and evaluated using the classical LMS, FLMS, kernel LMS, and proposed MFLMS adaptive filters. The simulation results for the time series with and without noise confirm the superiority and improvement in the prediction capability of the proposed MFLMS predictor over its counterparts.     

Experimental study of regional fractal speckle produced in large angle scattering

Using the interference of speckle and the spherical reference wave,we extract the real and the imaginary parts of the complex amplitudes of the speckle in large angle scattering.By calculating the spatial correlation functions of intensity,we find that the speckle has a property of regional fractality,i.e.the fractal exponent equals 1 in a small spatial region and it becomes less than 1 in a bigger region.The empirical analytic expression of the intensity correlation function is gained.The probability density distributions of the intensities and the complex amplitudes show that the regional fractal speckle still obeys zero-mean circular complex Gaussian statistics.     

Extraction of Parameters of Random Self-Affine Fractal Surfaces from Light Scattered Intensity by Levenberg-Marquardt Algorithm

A method for simultaneously extracting the parameters of self-affine fractal surfaces from a single experimental profile of scattered intensity data is proposed. The Levenberg-Marquardt algorithm is introduced to fit the theoretical equation for the scattering intensity profile to the experimental data. A precision system is designed for acquisition of scattering intensity data using the Boxcar integration technique. The surface parameters extracted （root-mean-square roughness w, lateral correlation length ζ, and roughness exponent α） are compared to those obtained using atomic force microscopy.     

Statistical properties of P-SV mode converted ultrasonic speckles reflected from an interface

The statistical properties of the mode converted SV wave speckles in the back scattering space were studied as ultrasonic P waves were incident on a strongly scattering interface. Based on the Frensel-Huygens theory and the correlation principle, the Rayleigh distribution of the SV wave speckle amplitude and the formula for calculating the average lateral size of the SV wave speckles were obtained. Besides, the probability density function of the normalized intensity of the SV wave speckles received by a transverse wave probe with an aperture of some size was deduced. The probability density function was related to the average number of the speckles received by the probe. Two transverse wave probes with apertures in different size were employed to measure the sound intensity of the SV wave speckles in the experiment. After the experimental data of the speckle intensity were analyzed statistically, it was shown that the experimental results were in good agreement with the theoretical ones. Thus, the presented theoretical conclusions were proved to be correct.     

Speckle reduction for medical ultrasound images with an expectation-maximization framework

In view of inherent speckle noise in medical images,a speckle reduction method was proposed based on an expectation-maximization(EM) framework.First,the real component of the in-phase/quadrature(I/Q) ultrasound image is extracted.Then,it is used to blindly estimate the point spread function(PSF) of the imaging system.Finally,based on the EM framework,an iterative algorithm alternating between the Wiener Filter and the anisotropic diffusion(AD) is exploited to produce despeckled images.The comparison experiment is carried out on both simulated and in vivo ultrasound images.It is shown that,with respect to the I/Q image,the proposed method averagely improves the speckle-signal-to-noise ratio(S-SNR) and the edge preservation index(β) of images by the factor of 1.94 and 7.52.Meanwhile,it averagely reduces the normalized mean-squared error(NMSE) by the factor of 3.95.The simulation and in vivo results indicates that the proposed method has a better overall performance than exited ones.