共查询到17条相似文献,搜索用时 156 毫秒
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在基于哈特曼-夏克波前传感器(SH-WFS)的自适应光学系统中,通常采用质心算法探测点源信标的子孔径光斑偏移量.然而质心算法探测精度受到诸如减阈值等因素的影响,在低信噪比(SNR )时不能准确估计光斑质心位置,而相关哈特曼算法不需要减阈值,具有更好的鲁棒性.本文在介绍相关SH-WFS基本原理的基础上,通过建立基于点源信标探测的相关SH-WFS算法的随机噪声模型,推导了光斑偏移测量误差表达式,系统分析了光子噪声、CCD读出噪声、背景光子噪声等因素对相关SH-WFS测量误差的影响.并进行了数值仿真及实验,仿真
关键词:
相关哈特曼-夏克波前传感器
相关哈特曼算法
质心算法
测量误差 相似文献
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自适应光学系统的数值模拟:噪音和探测误差的效应 总被引:1,自引:1,他引:0
噪音和探测误差是影响自适应光学系统性能的三个主要因素之一。噪音和探测误差使哈特曼-夏克(Hartmann-Shack)波前传感器所测得的华斜量产生误差,进而影响整个自适应光学系统的性能,建立了对噪声和探测误差对哈特曼-夏克波前传感器的影响进行数值模拟的理论模型,编制了计算程序,与已有的激光大气传输与自适应光学系统的计算程序相衔接,进行了模拟计算,对有限的离散采样,读出噪音和光子噪音的效应作了数值模拟研究,获得了一些对于实际的自适应光学系统的最佳设计有价值的结果。 相似文献
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哈特曼波前探测及波前校正的仿真与误差分析 总被引:3,自引:1,他引:2
报道了以37单元自适应光学系统为原型的波前校正计算机仿真模型,讨论了系统波前哈特曼探测误差,拟合误差以及变形镜波前复原误差,提出了自适应光学系统在校正大气湍流引直怕波前位相畸变时存在最佳有效孔径的设想。 相似文献
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基于目标和点扩展函数联合估计的点源目标图像近视解卷积 总被引:4,自引:7,他引:4
在传统的基于波前探测的解卷积方法中,由波前探测得到的点扩展函数被认为是精确的,并用维纳滤波进行复原,但是点扩展函数不可避免地存在误差,所以最终的复原目标图像质量不佳.为了解决该难题,提出了基于目标和点扩展函数联合估计的图像近视解卷积算法.它运用了点扩展函数和目标的先验信息,对点扩展函数和目标进行了规整和进一步约束,从而得到更优的恢复图像质量.对该方法的原理和实现过程进行了阐述,并将其运用于室内点源目标数据中.实验结果证明,与维纳滤波方法相比,该方法使图像恢复的效果得到明显改善. 相似文献
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在大气湍流条件较好而被探测信标光信号极弱的工作条件下,自适应光学系统在实际的应用中需要采用子孔径合并的部分校正方式。本文针对云南天文台1.2m高分辨率自适应光学系统中的哈特曼-夏克(Hartmann-Shack )波前传感器结构,从光子起伏噪声和CCD像素读出噪声对子孔径内哈特曼光斑质心探测精度的影响的角度,对子也径软件合并和硬件合并两种方案进行了理论分析和计算,导出了有实际应用意义的结论。 相似文献
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介绍了一种波前解卷积中噪声抑制规整化的新方法,并将此方法应用于室内模拟点源实验中。该方法通过在图像复原算法中增加针对图像高频部分的限制条件来抑制高频噪声,以达到对图像复原问题病态特性的规整化。实验结果表明:该规整化方法可以有效地抑制解卷积过程中高频噪声的影响,恢复出达到理论衍射极限分辨率的图像。对于噪声水平较高的降质图像,通过这种解卷积方法可以有效地提高信噪比。同维纳逆滤波方法相比,该方法可以在有效抑制导致病态的高频噪声的基础上充分保持图像的低频;与基于贝叶斯估计的近视解卷积算法相比,该方法不需要知道噪声水平或噪声类型等先验知识,只是从噪声本质出发,通过抑制降质图像高频部分,有效地解决了病态特性问题。 相似文献
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基于波前梯度的二阶矩和修正后的远场强度分布近似呈线性关系,设计了一种基于模型的无波前探测自适应光学系统快速闭环控制算法。使用61单元变形镜、CCD成像器件等建立了自适应光学系统仿真平台,并以不同湍流强度下的波前像差作为校正对象,分析了这种基于模型的无波前探测自适应光学系统的收敛速度、校正能力及对不同像差的适应性。结果表明,基于模型的无波前探测自适应光学系统在快速收敛的同时,能够获得接近波前校正器件的理想校正能力。N阶模式像差校正时,系统只需要进行N+1次远场光斑的测量。和现有的各种无波前探测自适应光学系统控制算法相比较,基于模型的无波前探测自适应光学系统所需的测量次数大大减少。 相似文献
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Real-time blind deconvolution of retinal images in adaptive optics scanning laser ophthalmoscopy 总被引:1,自引:0,他引:1
With the use of adaptive optics (AO), the ocular aberrations can be compensated to get high-resolution image of living human retina. However, the wavefront correction is not perfect due to the wavefront measure error and hardware restrictions. Thus, it is necessary to use a deconvolution algorithm to recover the retinal images. In this paper, a blind deconvolution technique called Incremental Wiener filter is used to restore the adaptive optics confocal scanning laser ophthalmoscope (AOSLO) images. The point-spread function (PSF) measured by wavefront sensor is only used as an initial value of our algorithm. We also realize the Incremental Wiener filter on graphics processing unit (GPU) in real-time. When the image size is 512 × 480 pixels, six iterations of our algorithm only spend about 10 ms. Retinal blood vessels as well as cells in retinal images are restored by our algorithm, and the PSFs are also revised. Retinal images with and without adaptive optics are both restored. The results show that Incremental Wiener filter reduces the noises and improve the image quality. 相似文献
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As it is not possible to obtain an accurate point spread function (PSF) in remote sensing imaging, classic deconvolution methods such as Wiener filtering often introduce strong noise and ringing artifacts, which contaminate the restored images. In this paper, we modify the standard Richarson-Lucy (RL) algorithm with a piecewise local regularization term and combine it with residual deconvolution method. Experimental results show that it is effective in suppressing negative effects, and images with rich details and sharp edges are obtained. 相似文献
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《Ultrasonics》2013,53(1):36-44
Vibro-acoustography (VA) is a medical imaging method based on the difference-frequency generation produced by the mixture of two focused ultrasound beams. VA has been applied to different problems in medical imaging such as imaging bones, microcalcifications in the breast, mass lesions, and calcified arteries. The obtained images may have a resolution of 0.7–0.8 mm. Current VA systems based on confocal or linear array transducers generate C-scan images at the beam focal plane. Images on the axial plane are also possible, however the system resolution along depth worsens when compared to the lateral one. Typical axial resolution is about 1.0 cm. Furthermore, the elevation resolution of linear array systems is larger than that in lateral direction. This asymmetry degrades C-scan images obtained using linear arrays. The purpose of this article is to study VA image restoration based on a 3D point spread function (PSF) using classical deconvolution algorithms: Wiener, constrained least-squares (CLSs), and geometric mean filters. To assess the filters’ performance on the restored images, we use an image quality index that accounts for correlation loss, luminance and contrast distortion. Results for simulated VA images show that the quality index achieved with the Wiener filter is 0.9 (when the index is 1.0 this indicates perfect restoration). This filter yielded the best result in comparison with the other ones. Moreover, the deconvolution algorithms were applied to an experimental VA image of a phantom composed of three stretched 0.5 mm wires. Experiments were performed using transducer driven at two frequencies, 3075 kHz and 3125 kHz, which resulted in the difference-frequency of 50 kHz. Restorations with the theoretical line spread function (LSF) did not recover sufficient information to identify the wires in the images. However, using an estimated LSF the obtained results displayed enough information to spot the wires in the images. It is demonstrated that the phase of the theoretical and the experimental PSFs are dissimilar. This fact prevents VA image restoration with the current theoretical PSF. This study is a preliminary step towards understanding the restoration of VA images through the application of deconvolution filters. 相似文献
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惯性约束聚变中环孔编码图像恢复的改进维纳滤波方法 总被引:7,自引:0,他引:7
针对惯性约束聚变(ICF)中环形孔径编码图像的恢复问题提出了一种改进的维纳滤波方法。在传统的维纳滤波方法中,由于原图像和噪声是未知的,故通常是用某一待定常量来代替其中的噪声与信号的谱密度之比。这种近似忽视了信号与噪声本身的信息,从而造成丢失某些关键的细节,难以达到高质量的图像复原效果。在改进的方法中,首先采用传统维纳滤波方法求得初始估值,然后利用该初始值求得原图像及噪声的谱密度估值,进而利用这些新获得的信息构成改进的维纳滤波器对退化图像进行第二次滤波。实验表明,这种改进方法可以克服原方法的不足,突出图像的一些关键细节,提高图像的整体质量。在仿真实验中,恢复图像的均方误差降低了15%以上;在实际惯性约束聚变图像的解码恢复实验中,图像恢复效果亦有显著改善。该方法还可以推广到其他图像恢复的应用中。 相似文献