Improved interframe registration based nonuniformity correction for focal plane arrays

In this paper, an improved interframe registration based nonuniformity correction algorithm for focal plane arrays is proposed. The method simultaneously estimates detector parameters and carries out the nonuniformity correction by minimizing the mean square error between the two properly registered image frames. A new masked phase correlation algorithm is introduced to obtain reliable shift estimates in the presence of fixed pattern noise. The use of an outliers exclusion scheme, together with a variable step size strategy, could not only promote the correction precision considerably, but also eliminate ghosting artifacts effectively. The performance of the proposed algorithm is evaluated with clean infrared image sequences with simulated nonuniformity and real pattern noise. We also apply the method to a real-time imaging system to show how effective it is in reducing noise and the ghosting artifacts.     

A two-frame approach for scene-based nonuniformity correction in array sensors

This paper introduces a new scene-based technique to correct the fixed-pattern noise (FPN) in array sensors. This method registers a pair of image frames exhibiting small relative scene translation and then the noise pattern can be reconstructed using the constrained least-squares estimation. The key advantage of this technique is that the accurate estimates of the bias nonuniformity can be obtained with only two images, without imposing any assumptions on the structure of the FPN. Besides, the method works on almost static scene, and therefore does not require larger scale global motion and statistical assumptions on the scene irradiance. We test our method on synthetically generated FPN as well as with real infrared data, and experimental results demonstrate the significant reduction in FPN, validating the effectiveness of our approach. Finally, we validate the feasibility and validity of using the proposed method as a first step fostering the success of more sophisticated registration-based time-evolving correction algorithms.     

Efficient single image stripe nonuniformity correction method for infrared focal plane arrays

We present a novel, stripe nonuniformity correction algorithm for infrared focal plane arrays. This method relies on the separation of nonuniformity and true scene, and the nonuniformity correction parameter is obtained by traversing the error function of two adjacent columns?? pixels in local template window. Based on the succession of two adjacent columns?? correlation, the stripe nonuniformity correction can be achieved in a single frame. Experimental results, to illustrate the performance of the method, include the use of infrared image sequences with simulated nonuniformity and a diverse set of real IR imagery.     

Scene based nonuniformity correction based on block ergodicity for infrared focal plane arrays

This paper puts forward a new scene based nonuniformity correction algorithm for IRFPA. This method adopts phase-correlation method for motion estimation and takes the sum of mean-square errors of the pixel brightness between several adjacent frames as the cost function when the brightness constancy assumption between two adjacent frames is satisfied. Nonuniformity correction parameters could be estimated by minimizing such cost function. In order to reduce calculation quantity, we can divide these images into several subblocks, and solve for the optimum solution of the cost function respectively in each subblock. From the analysis, it is shown that the optimum solution is of global uniqueness when all the elements in subblocks could satisfy the ergodicity condition. Then the estimated value of nonuniformity correction parameters could be deduced by minimizing the cost functions. The nonuniformity correction experiments for both infrared image sequence with simulated nonuniformity and infrared imagery with real nonuniformity show that the proposed algorithm could achieve a great correction effect by only analyzing a small number of frames.     

基于自适应扩散模型的单帧红外条纹非均匀性校正算法

针对红外焦平面成像系统存在列向条纹非均匀性的现象,采用了一种基于自适应PM扩散模型的非均匀校正新算法。首先,综合利用图像梯度信息和局部灰度统计信息,自适应计算PM模型的扩散阈值;然后将每列像素的PM模型估计值作为该列像素的期望值;最后采用最陡下降法迭代计算得到每列像元的校正参数,并对结果进行循环校正以提高校正效果。实验结果表明:该算法可以保护图像边缘信息,与同类算法相比,能够更有效地抑制条纹非均匀性,并且能够防止图像产生鬼影。     

A new adaptive nonuniformity correction algorithm for infrared line scanner based on neural networks

The striping pattern nonuniformity of the infrared line scanner (IRLS) severely limits the system performance. An adaptive nonuniformity correction (NUC) algorithm for IRLS using neural network is proposed.It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that the algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.     

Nonuniformity correction algorithm based on adaptive filter for infrared focal plane arrays

Response nonuniformity is a key problem that influences the imaging performance of infrared focal plane arrays (IRFPA) imaging system. A parallel processing algorithm to adaptively estimate the nonuniformity correction (NUC) parameters for IRFPA is presented. In this algorithm, a bank of the adaptive filter is applied to adaptively estimate the NUC parameters for every detector in IRFPA. The infrared image sequences are input into the bank of adaptive filter. After certain times recursion calculations are executed frame-by-frame, then the optimal coefficients of the gain and the offset of detector in IRFPA are achieved. Then the NUC is fulfilled ultimately. The algorithm reduces the influence that the response drift with time imposed on NUC effectively, and achieves good NUC effect. It was validated by real experimental imaging procedures.     

Minimum mean square error method for stripe nonuniformity correction

Stripe nonuniformity is very typical in line infrared focal plane (IRFPA) and uncooled starring IRFPA. We develop the minimum mean square error (MMSE) method for stripe nonuniformity correction (NUC). The goal of the MMSE method is to determine the optimal NUC parameters for making the corrected image the closest to the ideal image. Moreover, this method can be achieved in one frame, making it more competitive than other scene-based NUC algorithms. We also demonstrate the calibration results of our algorithm using real and virtual infrared image sequences. The experiments verify the positive effect of our algorithm.     

Ghosting reduction in scene-based nonuniformity correction of infrared image sequences

Scene-based adaptive nonuniformity correction （NUC） is currently being applied to achieve higher performance in infrared imaging systems. However, almost all scene-based NUC algorithms cause the production of ghosting artifacts over output images. Based on constant-statistics theory, we propose a novel threshold self-adaptive ghosting reduction algorithm to improve the space low-pass and temporal high-pass （SLP- THP） NUC technique. The correction parameters of the previous frame are regarded as thresholds to compute new correction parameters. Experimental results show that the proposed algorithm can obtain a satisfactory performance in reducing unwanted ghosting artifacts.     

Three-step nonuniformity correction for a highly dynamic intensified charge-coupled device star sensor

A three-step nonuniformity correction algorithm based on the photoelectrical response models of intensified charge-coupled device (ICCD) for a highly dynamic ICCD star sensor is proposed in the current paper. The influence factors of nonuniformity correction precision are analyzed based on the photoelectrical imaging theory. The photoelectrical response models of ICCD are obtained using the experimental method, and the nonuniformity correction is implemented in three steps based on the photoelectrical response models. The nonuniformity correction results in constant-radiance images and sky images of the highly dynamic star sensor show that the proposed algorithm has satisfactory correction precision, and the accuracy of the highly dynamic star sensor can be enhanced effectively when sky images are processed using the three-step nonuniformity correction algorithm.     

Test and evaluation of reference-based nonuniformity correction methods for microbolometer infrared detectors

In the paper, reference-based nonuniformity correction methods for microbolometer infrared detectors are discussed and tested. In order to evaluate their effectiveness, a complete readout circuit for amorphous silicon microbolometer focal plane array has been designed. The tests were carried out on a developed stand including several extended blackbodies. Some modification of standard two-point correction algorithm incorporating detectors response at external shutter to compensate offset drift is also proposed. The obtained results are presented.     

Beamforming correction for dipole measurement using two-dimensional microphone arrays

In this paper, a beamforming correction for identifying dipole sources by means of phased microphone array measurements is presented and implemented numerically and experimentally. Conventional beamforming techniques, which are developed for monopole sources, can lead to significant errors when applied to reconstruct dipole sources. A previous correction technique to microphone signals is extended to account for both source location and source power for two-dimensional microphone arrays. The new dipole-beamforming algorithm is developed by modifying the basic source definition used for beamforming. This technique improves the previous signal correction method and yields a beamformer applicable to sources which are suspected to be dipole in nature. Numerical simulations are performed, which validate the capability of this beamformer to recover ideal dipole sources. The beamforming correction is applied to the identification of realistic aeolian-tone dipoles and shows an improvement of array performance on estimating dipole source powers.     

Photonic true-time delay unit for broadband adaptive nulling in antenna arrays

An Opto-VLSI-based (VLSI: very-large-scale-integration) tunable true-time delay (TTD) generation unit used for adaptive null steering in phased array antennas is presented. The system is based on continuous tunable optical TTD technique. Arbitrary multiple true-time delays to generate multiple broadband nulls can simultaneously be synthesised for each antenna element. The proposed structured are characterised both theoretically and experimentally. Experimental results demonstrating the principle of the true-time delay for null generations are presented. The maximum time delay measured for a wavelength tuning from 1530 to 1560 nm is 9.5 ns.     

Efficiency of signal processing for spatially distributed sources in adaptive antenna arrays

The potential efficiency of signal processing for spatially distributed noise sources in adaptive antenna arrays is analyzed. The behavior of the output signal-to-noise ratio is studied as a function of the transverse space correlation radius, the antenna aperture, and the noise power.Nizhni Novgorod State University. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 36, No. 6, pp. 512–519, June, 1993.     

Nonuniformity correction algorithm with nonlinear model for infrared focal plane arrays

For the detector in infrared focal plane arrays (IRFPA) with a large dynamic range of response, a nonlinear model of response curve of the detector in IRFPA is introduced in this paper. With the model, the Kalman-filter nonuniformity correction (NUC) algorithm with linear model, developed by Torres and Hayat, is extended. In the extended algorithm, the raw image is translated into a linearized one firstly by directly employing a logarithm-based transformation. Then the linearized image is corrected by the Kalman-filter NUC algorithm with linear model, and the corrected linearized image is obtained. Finally the uniformity image of the original one is achieved by fulfilling an exponent transformation to the corrected linearized image. The presented algorithm not only inherits the advantage of the original algorithm that resolves the problem of the temporal drift in the gain and the bias in each detector by updating NUC parameters with information of the current scene, but also reduce the influence of the detector nonlinear response to the NUC performance, so it is suitable for IRFPA under large response-range. The NUC ability of the presented algorithm is demonstrated by experiments with real infrared image sequences.     

自适应光学的时域部分校正

导出闭环伺服系统采用ＲＣ滤波器的自适应光学望远镜的带宽表达式，对风速不随高度变化及赝风速度在所有高度上都超过自然风速这两种重要的特殊情况，讨论了系统带宽与校正后剩余波前方差或斯特列尔比（ＳＲ）之间的关系。结果表明，对前一种情况，几十至一百Ｈｚ的带宽已足够；而对后一种情况，也许需要数百乃至上千Ｈｚ的带宽。     

Sequence of phase correction in multiconjugate adaptive optics

The way in which the sequence of phase correction impinges on performance in multiconjugate adaptive optics systems is described. When multiple phase modulators with different conjugate ranges are used, the conjugate images of the phase modulators in the atmosphere must be reimaged in the reverse order post focus, and adaptive phase correction applied in this sequence for perfect amplitude and phase cancellation. Performing the correction without relay optics results in residual amplitude and phase aberrations. It is shown, by Monte Carlo simulations of Fresnel propagation, that the effects of wave optical propagation become nonnegligible at visible wavelengths and for large air masses.     

全变分引导的双边滤波图像去噪方法

双边滤波是一种结合了图像空间邻近度和像素值相似度的非线性滤波方法。当噪声水平较小时,使用输入的待去噪图像来引导双边滤波核函数权重的计算较为可行,但当噪声水平变大时,噪声图像的结构信息被严重破坏,影响了双边滤波器中值域核函数权值的准确计算。提出了全变分引导的双边滤波图像去噪方法,给出其Split Bregman快速算法。利用全变分模型对噪声图像进行光滑,得到一幅包含清晰结构信息的图像,将图像作为双边滤波的引导图像进行计算,对上述过程进行迭代处理以提高算法的稳定性。实验表明,提出得算法不仅在主观视觉效果上优于双边滤波,客观评价指标PSNR值也较双边滤波提高了1.5dB左右;在较好去除噪声的同时较好地保持了边缘结构。     

Methods for determination of weight vector of adaptive arrays with short samples

Methods are proposed for determination of the weight vector in adaptive antenna arrays (AA) in the case of a short input-process sample, when the number of sampled vectors is smaller than the number of AA elements and an inverted correlation matrix of the interference in the AA receiving channels does not exist.Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 37, No. 4, pp. 493–509, April, 1994.