Blind deconvolution: multiplicative iterative algorithm

A new algorithm has been developed for performing blind deconvolution on degraded images. The algorithm naturally preserves the nonnegative constraint on the iterative solutions of blind deconvolution and can produce a restored image of high resolution. Furthermore, benefiting from the multiplicative form, the algorithm is free from the instability of numerical computation. Results of applying the algorithm to simulated and real degraded images are reported.     

Blind image deconvolution using sparse and redundant representation

This work devotes to the image deconvolution problem that restores clear image from its blurred and noisy measurements with little prior about the blur. A deconvolution method based on sparse and redundant representation theory is developed in this paper. It firstly represents the blur and image over different redundant dictionaries and imposes sparsity constraint to their representation coefficients respectively, then alternately estimates them using an iterative algorithm employing optimization technique. Experimental results on astronomical images show that the proposed method can achieve as good performance as the method requiring a known blur, which demonstrates its effectiveness.     

Blind image deconvolution with spatially adaptive total variation regularization

A blind deconvolution algorithm with spatially adaptive total variation regularization is introduced. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish edges from flat areas. The proposed algorithm can effectively reduce the noise in flat regions as well as preserve the edge and detailed information. Moreover, it becomes more robust with the change of the regularization parameter. Comparative results on simulated and real degraded images are reported.     

Blind image deconvolution using the Fields of Experts prior

In this paper, we present a method for single image blind deconvolution. To improve its ill-posedness, we formulate the problem under Bayesian probabilistic framework and use a prior named Fields of Experts (FoE) which is learnt from natural images to regularize the latent image. Furthermore, due to the sparse distribution of the point spread function (PSF), we adopt a Student-t prior to regularize it. An improved alternating minimization (AM) approach is proposed to solve the resulted optimization problem. Experiments on both synthetic and real world blurred images show that the proposed method can achieve results of high quality.     

Blind image deconvolution subject to bandwidth and total variation constraints

We present a maximum likelihood (ML) deconvolution algorithm with bandwidth and total variation (TV) constraints for degraded image due to atmospheric turbulence. The bandwidth limit function is estimated in view of optical system parameters and Fourier optical theory. With the aid of bandwidth and TV minimization as compelling constraints, the algorithm can not only suppress noise effectively but also restrict the bandwidth of point-spread function (PSF) that may lead to trivial solution. Compared with the conventional ML method, the proposed algorithm is able to restore a noise-free image, and the detailed texture is better than that of ML.     

斜坡海底波导中随机声源的信道盲解卷积

该文研究了在斜坡海底环境中,通过基于射线的盲解卷积(RBD)方法,利用随机声源发出的信号来估计信道响应(CIR)的有效性,并讨论了不同信噪比和海底坡度情况下,RBD估计到的CIR与CIR理论值的相关性,对2016年美国圣巴巴拉海峡实验进行了仿真验证。RBD方法通过宽带波束形成估计随机声源的相位,以得到声源和接收阵之间的CIR。仿真结果表明,斜坡海底情况下RBD方法仍能较为准确地估计信道的CIR,噪声和海底坡度的变化均会对RBD估计到的CIR的精确度产生一定的影响。在具有一定粗糙度的斜坡海底波导或存在海底山丘的波导中,RBD仍然可以对CIR进行有效估计。     

Blind deconvolution for robust signal estimation and approximate source localization

Synthetic time reversal (STR) is a technique for blind deconvolution in an unknown multipath environment that relies on generic features (rays or modes) of multipath sound propagation. This paper describes how ray-based STR signal estimates may be improved and how ray-based STR sound-channel impulse-response estimates may be exploited for approximate source localization in underwater environments. Findings are based on simulations and underwater experiments involving source-array ranges from 100 m to 1 km in 60 -m-deep water and chirp signals with a bandwidth of 1.5-4.0 kHz. Signal estimation performance is quantified by the correlation coefficient between the source-broadcast and the STR-estimated signals for a variable number N of array elements, 2 ≤ N ≤ 32, and a range of signal-to-noise ratio (SNR), -5 dB ≤ SNR ≤ 30 dB. At high SNR, STR-estimated signals are found to have cross-correlation coefficients of ～90% with as few as four array elements, and similar performance may be achieved at a SNR of nearly 0 dB with 32 array elements. When the broadband STR-estimated impulse response is used for source localization via a simple ray-based backpropagation scheme, the results are less ambiguous than those obtained from conventional broadband matched field processing.     

Blind image deconvolution using the zero-lag slice of higher-order statistics

A novel algorithm for blind image deconvolution using the zero-lag slice (ZLS) of higher-order statistics only is presented. This method first estimates the point-spread function (PSF) using the ZLS of its third-order moment (TOM) and then uses it with one of the known classical image deconvolution methods. The proposed method has simple computations for PSF estimation because it solves a nonlinear problem by using an iterative method with fast convergence. In each iteration, one need only calculate the ZLS of the TOM and estimate the PSF using simple two-dimensional operations. Furthermore, the method presented achieves good results, since the ZLS estimate obtained from the degraded image exhibits high reliability. The good performance of the proposed algorithm is demonstrated by applying it to synthetic and real data sets.     

基于总变分的湍流退化噪声图像盲反卷积复原

根据总变分的噪声抑制特性和大气湍流成像过程,建立了基于总变分的大气湍流噪声图像多帧盲反卷积复原最小化模型,以基于共轭梯度数值优化方法的交替迭代算法求解,复原出了观测目标的清晰图像。在计算机上模拟了湍流退化和噪声污染图像。实验结果表明,该复原算法能有效地克服大气湍流和噪声的影响,可复原出清晰的原始目标图像。     

Blind deconvolution of audio-frequency signals using the self-deconvolving data restoration algorithm

A signal processing algorithm has been developed in which a filter function is extracted from degraded data through mathematical operations. The filter function can be used to restore much of the degraded content of the data through use of a deconvolution process. The operation can be performed without prior knowledge of the detection system, a technique known as blind deconvolution. The extraction process, designated self-deconvolving data reconstruction algorithm, is applied here to audio-frequency signals showing significant qualitative improvement. Degradation arising from the process of electronic recording and reproduction is significantly reduced.     

基于垂直阵模态分解的低频水声信号盲解卷处理研究

研究了基于人工时反处理的水声信号盲解卷方法,并在此基础上提出了一种基于简正波模态分解的低频水声信号的盲解卷处理方法。该方法适用于浅海波导中垂直阵接收的远程低频水声信号的盲解卷处理。该方法首先从浅海中垂直阵接收的信号中提取(估计)出波导中传播的简正波模态函数信息,然后,根据估计的模态函数信息通过模态滤波来实现水声信道盲解卷处理。针对典型的浅海波导环境,进行了计算机仿真试验,结果表明:(1)远程低频条件下,模态分解方法可以从垂直阵接收的信号中提取出波导中有效传播的模态函数信息,因此这种方法解决了目前人工时反处理方法需要准确的模态函数先验信息的问题;(2)在一定带宽条件下,接收信号信噪比较低时,本文给出的这种基于模态滤波的盲解卷方法比人工时反处理具有更好的解卷性能。     

Flow rate limitation in open wedge channel under microgravity

A study of flow rate limitation in an open wedge channel is reported in this paper. Under microgravity condition, the flow is controlled by the convection and the viscosity in the channel as well as the curvature of the liquid free surface. A maximum flow rate is achieved when the curvature cannot balance the pressure difference leading to a collapse of the free surface. A 1-dimensional theoretical model is used to predict the critical flow rate and calculate the shape of the free surface. Computa- tional Fluid Dynamics tool is also used to simulate the phenomenon. Results show that the 1-dimensional model overestimates the critical flow rate because extra pressure loss is not included in the governing equation. Good agreement is found in 3-dim- ensional simulation results. Parametric study with different wedge angles and channel lengths show that the critical flow rate increases with increasing the cross section area; and decreases with increasing the channel length. The work in this paper can help understand the surface collapsing without gravity and for the design in propellant management devices in satellite tanks.     

Noncoherent deconvolution

A noncoherent optical system has been devised to perform deconvolution. A transparency of a bar chart convolved with a Gaussian function is operated upon by a set of suitably weighted Young slits positioned in the entrance pupil of a camera lens. The resulting image shows some degree of deconvolution with a measurable increase in edge slope. Microdensitometer tracings of convolved object and deconvolved image are presented.     

Electronic band structure of calcium selenide under pressure

Energy band structures under pressure of calcium selenide (CaSe) were calculated using the plane-wave pseudopotential code CASTEP. The results show a progressive transition from a direct to an indirect gap semiconductor at a pressure of about 2 GPa, in the B1 phase. An insulator-conductor change was also observed at 70 GPa, in the B2 phase. Concerning CaSe, these two results could not be evidenced in previous literature. Hence, our work is a first attempt in this direction.     

Compact multiframe blind deconvolution

We describe a multiframe blind deconvolution (MFBD) algorithm that uses spectral ratios (the ratio of the Fourier spectra of two data frames) to model the inherent temporal signatures encoded by the observed images. In addition, by focusing on the separation of the object spectrum and system transfer functions only at spatial frequencies where the measured signal is above the noise level, we significantly reduce the number of unknowns to be determined. This "compact" MFBD yields high-quality restorations in a much shorter time than is achieved with MFBD algorithms that do not model the temporal signatures; it may also provide higher-fidelity solutions.     

Theoretical band structure calculation and superconductivity of NbC under pressure

Abstract

We report a theoretical calculation of the band structure and superconductivity of niobium carbide in the NaCl structure under pressure. The effect of pressure on the band structure is obtained by means of the self-consistent linear muffin-tin orbital method. The parameters necessary to calculate the superconducting transition temperature (T_c) are taken from our band structure results. The dependence of total energy on volume is calculated and is in good agreement with other earlier works. The calculated value of the cell parameter is in agreement with the experimental value (8.45 a.u). McMillan formula is used to calculate the value of T_c The calculated values of T_c are compared with the available experimental data.     

Nonlinear dynamic range compression deconvolution

We introduce a dynamic range image compression technique for nonlinear deconvolution; the impulse response of the distortion function and the noisy distorted image are jointly transformed to pump a clean reference beam in a two-beam coupling arrangement. The Fourier transform of the pumped reference beam contains the deconvolved image and its conjugate. In contrast to standard deconvolution approaches, for which noise can be a limiting factor in the performance, this approach allows the retrieval of distorted signals embedded in a very high-noise environment.     

A new emission band under high density excitation in alkali halides

A new emission band has been found in alkali halides under high density excitation produced by heavy ion bombardments and is suggested to be arised from the recombination of bi-excitons.