一种基于DFD的自动对焦算法

引入了一种基于DFD的自动对焦算法。通过这种算法,只要给定了两幅不同离焦位置的图像,就可由算法推导出目标物体的正确对焦位置,从而控制镜头完成自动对焦。实验表明,这种算法精度比较高,速度比较快,鲁棒性良好。     

使用柯西分布点扩散函数模型的单幅散焦图像深度恢复

目的 当前,大多数单幅散焦图像的3维(3D)场景深度恢复方法,通常使用高斯分布描述点扩散函数(PSF)模型,依据图像边缘散焦模糊量与场景深度的对应关系获得稀疏深度图,采用不同的扩展方法得到整个场景图像的全深度图.鉴于现有方法的深度恢复结果还不够精准,对各种噪声干扰还不够健壮,提出一种基于柯西分布的点扩散函数模型计算物体图像边缘散焦模糊量的方法.方法 将输入的单幅散焦图像分别用两个柯西分布重新模糊,利用图像边缘两次重新模糊图像间梯度比值和两个柯西分布的尺度参数,可以计算出图像中边缘处的散焦模糊量.使用matting内插方法将边缘模糊量扩展到整个图像,即可恢复场景的全深度图.结果 将原始Lenna图像旋转并加入高斯噪声以模拟图像噪声和边缘位置误差,用原图与噪声图比较了柯西分布图像梯度比值与高斯分布图像梯度比值的平均误差.使用多种真实场景图像数据,将本文方法与现有的多种单幅散焦图像深度恢复方法进行了比较.柯西分布图像梯度比值的平均误差要小于高斯分布图像梯度比值的平均误差.本文方法能够从非标定单幅散焦图像中较好地恢复场景深度,对图像噪声、不准确边缘位置和邻近边缘具有更好的抗干扰能力.结论 本文方法可以生成优于现有基于高斯模型等方法的场景深度图.同时,也证明了使用非高斯模型建模PSF的可行性和有效性.     

基于离焦深度法的自动对焦光路设计

基于离焦深度法设计了自动对焦光路,光路由激光 光源,准直扩束透镜,调焦透镜,摄 像头组成。使用ZEMAX软件模拟了对焦过程,通过控制调焦透镜的位置获取光斑半径,计算 对焦位置。 移动调焦透镜,分别在距离对焦目标5.62 cm,7.38 cm,14.02 cm,16.88 cm,20.94 cm处得到了弥散光斑 的直径。计算得到的误差在1mm以内。基于此,实际搭建了对焦光路并进行模拟。采用位移 滑轨模拟透 镜的变焦运动,由摄像头获取物面上的激光斑点,通过MATLAB编程来快速获得光斑直径的之 间的比例。 结果显示,对焦结果误差在1cm以内,考虑到导轨读数存在误差,摄像头像素有限,激光功 率不稳定等原 因,虽然实际结果与理论模拟之间存在差异,但证实了此方法的可行性。后续工作将用位移 平台替换手动 滑轨,编程精密控制透镜的移动位置,实现自动对焦。研究工作为改进本课题组已经开发的 便携式高灵敏 毒品荧光检测系统提供技术参考。     

Correction of autofocusing errors due to specimen tilt for automated electron tomography

Transmission electron microscopy images acquired under tilted‐beam conditions experience an image shift as a function of defocus settings – a fact that is exploited as a method for defocus determination in most of the automated tomography data collection systems. Although the method was shown to be highly accurate for a large variety of specimens, we point out that in its original design it can strictly only be applied to images of untilted samples. The application to tilted samples and thus in automated electron tomography is impaired mainly due to a defocus change across the images, resulting in reduced accuracy. In this communication we present a method that can be used to improve the accuracy of the basic autofocusing procedures currently used in systems for automated electron tomography.     

离焦模糊图像的维纳滤波复原研究

微操作中，显微视觉系统获取的图像通常是离焦模糊图像。离焦模糊图像的退化模型可用圆盘函数描述，利用模糊图像无方向性的二阶拉氏微分图像的自相关的负相关峰形成的环形槽的直径等于作为圆盘函数直径的2倍可以确定该函数。对模糊图像进行一次维纳滤波方法得到原图像的估计值，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，该方法计算量小、鉴别精度高、抗噪声能力较强，突出原图像的一些关键细节，提高了图像的复原质量。     

Defocus Hyperspectral Image Deblurring with Adaptive Reference Image and Scale Map

Journal of Computer Science and Technology - Defocus blur is one of the primary problems among hyperspectral imaging systems equipped with simple lenses. Most of the previous deblurring methods...     

近视防控离焦镜片像质评价方法的探讨

近视防控离焦镜片的光学性能评价的过程中,通常以镜片的屈光度地形图作为分析依据,对成像质量的影响目前研究较少.从像质评价入手,搭建了一套镜片?相机测试系统用于测量离焦镜片的光学传递函数(MTF).整个系统是由光源、成像模块、镜片夹持工具、棋盘标定板和MTF分析软件系统组成的.实验过程中对相机镜头、国内明月离焦镜片、国外Z...     

Confocal Stereo

We present confocal stereo, a new method for computing 3D shape by controlling the focus and aperture of a lens. The method is specifically designed for reconstructing scenes with high geometric complexity or fine-scale texture. To achieve this, we introduce the confocal constancy property, which states that as the lens aperture varies, the pixel intensity of a visible in-focus scene point will vary in a scene-independent way, that can be predicted by prior radiometric lens calibration. The only requirement is that incoming radiance within the cone subtended by the largest aperture is nearly constant. First, we develop a detailed lens model that factors out the distortions in high resolution SLR cameras (12MP or more) with large-aperture lenses (e.g., f1.2). This allows us to assemble an A×F aperture-focus image (AFI) for each pixel, that collects the undistorted measurements over all A apertures and F focus settings. In the AFI representation, confocal constancy reduces to color comparisons within regions of the AFI, and leads to focus metrics that can be evaluated separately for each pixel. We propose two such metrics and present initial reconstruction results for complex scenes, as well as for a scene with known ground-truth shape. Part of this work was done while the authors were visiting Microsoft Research Asia, in the roles of research intern and Visiting Scholar respectively.     

Real‐Time Defocus Rendering With Level of Detail and Sub‐Sample Blur

This paper presents a GPU‐based rendering algorithm for real‐time defocus blur effects, which significantly improves the accumulation buffering. The algorithm combines three distinctive techniques: (1) adaptive discrete geometric level of detail (LOD), made popping‐free by blending visibility samples across the two adjacent geometric levels; (2) adaptive visibility/shading sampling via sample reuse; (3) visibility supersampling via height‐field ray casting. All the three techniques are seamlessly integrated to lower the rendering cost of smooth defocus blur with high visibility sampling rates, while maintaining most of the quality of brute‐force accumulation buffering.     

The role of Poisson's binomial distribution in the analysis of TEM images

Frank's observation that a TEM bright-field image acquired under non-stationary conditions can be modeled by the time integral of the standard TEM image model [J. Frank, Nachweis von objektbewegungen im lichtoptis- chen diffraktogramm von elektronenmikroskopischen auf- nahmen, Optik 30 (2) (1969) 171–180.] is re-derived here using counting statistics based on Poisson's binomial distribution. The approach yields a statistical image model that is suitable for image analysis and simulation.