一种改进的数字图像清晰度评价函数研究

图像自动聚焦时，由于噪声和不同光照条件影响图像质量，实时评价图像清晰度效果较差。本文比较了能量梯度函数、频谱函数、灰度熵函数、灰度变化函数评价图像清晰度的优劣，提出了一种改进的能量梯度闽值方法评价图像清晰度，建立了数学模型，并给出了三种不同物体的数字图像聚焦重复精度的试验结果和分析。试验结果表明：实时评价图像清晰度该方法速度快，计算量小，信噪比高，可靠性好，聚焦重复精度高。     

基于小波多分辨率分析的自动聚焦算法

利用点扩散函数（PSF）理论讨论了自动聚焦过程中图像高频能量的变化。通过对传统方差评价函数的改进,提出了一种新的自动聚焦算法。该算法利用小波多分辨率分析突出图像高频能量,改善了聚焦的精确度和鲁棒性。同传统的图像灰度方差法和梯度法评价函数相比,本评价函数具有更好的单峰性、尖锐性和准确性。     

一种光学显微自动聚焦系统设计与实现

针对普通CCD拍摄的低对比度生物样品图像,设计并实现了一种以PC机为控制核心的光学显微镜自动聚焦系统。系统采用弹性联轴器与显微镜调焦轴直接耦合的方式,结合细分驱动,有效地消除了传动机构的回程差,提高了聚焦控制精度。在对几种常用图像清晰度评价算子进行分析的基础上,证实了图像自相关算子是评价低对比度生物样品图像清晰度的有效算法。实验结果表明,该系统自动聚焦的准确度和实时性基本上满足生物学研究的需要。     

基于FPGA的步进电机驱动及自动聚焦的实现

基于Xilinx公司的Spartan-IIE系列FPGA XC2S300E-6-PQ208C完成了一种聚焦马达驱动及自动聚焦的完整设计。该设计接收CCD图像传感器套件输出的图像信号,采用一种改进的灰度差分法作为聚焦评价函数,即将一场图像的所有像素的亮度值与周围像素的亮度值差的绝对值的和作为聚焦评价函数,根据相邻同场的聚焦评价函数的比较结果,配合相应的搜索策略来控制步进电机的转动方向,实现图像的自动聚焦。实际实现的聚焦效果优于改进前的聚焦算法。     

一种摄像头自动聚焦方法及硬件实现

提出了一种基于数字图像处理技术实现自动聚焦的方法,给出了一种改进的灰度差分法作为图像聚焦是否清楚的评价函数。对图像质量进行比较,根据比较结果由单片机驱动镜头到达聚焦点,实现自动聚焦。     

数字图像清晰度评价函数的研究与改进

通过分析常见的图像清晰度评价函数,针对自动对焦系统中图像清晰度评价问题,提出了一种基于聚焦窗口的改进梯度评价函数算法。改进后的算法具有计算量小、实时性好、评价曲线单峰性好、灵敏度高、聚焦检测效率高等特点,可以更好地满足自动对焦系统对图像清晰度评价的要求。     

基于十字线灰度图像清晰度模型的构建与应用

针对图像清晰(聚焦)度评价函数种类多、计算复杂、尚无统一标准的现状,构建一种十字线灰度图像清晰(聚焦)度评价的理论模型,分析实际应用中理论模型存在的问题,然后提出图像清晰(聚焦)度评价改进模型.实验表明:清晰(聚焦)度评价改进模型符合十字线灰度图像实际,具有应用价值.     

快速自动聚焦算法在影像精密测高中的应用

快速、有效地实现聚焦是图像法测高的焦点,选择合适的焦点评价函数和设计高效的图像自动聚焦算法是其中的关键问题。在比较研究图像评价函数的基础上,选择灰度方差作为焦点评价函数,研究了一种粗略试探和微步距精确搜索相结合的自动聚焦算法,并分析了影像聚焦精度和速度的影响因素。该聚焦算法应用于自动影像测量仪,通过对各种材质的表面在变倍镜头的不同倍率下做聚焦和测高试验,获得结果并进行了详细的比较分析。结果表明,该算法稳定、可靠、高效,测量结果精确。     

结构光测量自动聚焦系统开发和研究

为配合结构光测量系统来进行更深入的处理和测量,在以PC机为控制核心的基础上设计了一种自动聚焦系统,以实现对不同场景图像的亮度自动调节和精确聚焦功能。系统以Sobel-Tenengrad函数为评价函数,通过登山法搜索极值,在10 s内完成精确聚焦。通过该系统在不同场景下对四种灰度评价函数值进行计算,对其单峰性和鲁棒性进行分析和总结,经过实验后发现Sobel-Tenengrad函数、梯度向量平方函数、拉普拉斯函数综合性能良好,而方差函数未能表现出评价函数应具有的性能。     

显微镜一种新的自动聚焦算法

在开发普通光学显微镜自动聚焦系统的过程中,超初作者采用图像灰度熵和灰度方差这两种常用的显微镜聚焦算法,但实际应用效果不很理想。经检验发现了两种算法的一些不足之处,并针对这些不足点加以改进,进而提出了灰度差分绝对值之和算法。经实际聚焦过程中的对比实验,证明了新算法在聚焦可靠性、聚焦速度及聚焦结果等方面都具有一定的优越性。     

Shape from focus

The shape from focus method presented here uses different focus levels to obtain a sequence of object images. The sum-modified-Laplacian (SML) operator is developed to provide local measures of the quality of image focus. The operator is applied to the image sequence to determine a set of focus measures at each image point. A depth estimation algorithm interpolates a small number of focus measure values to obtain accurate depth estimates. A fully automated shape from focus system has been implemented using an optical microscope and tested on a variety of industrial samples. Experimental results are presented that demonstrate the accuracy and robustness of the proposed method. These results suggest shape from focus to be an effective approach for a variety of challenging visual inspection tasks     

嵌入式视频显微镜自动调焦控制系统设计

针对视频显微镜手动调焦效率低、精度差、难以得到最佳显微图像的现状,设计了一种基于嵌入式开发和Matlab数字图像处理的自动调焦控制系统.通过在显微镜调焦、变倍手轮和光照调节处添加精密传动机构,并由单片机电路控制部分实现计数脉冲的获取和电机的控制;所获序列显微图像经电荷耦合器件(CCD)镜头传至PC系统,并由Matlab图像处理软件对其进行清晰度判定,结合设计的取均值约束二次调焦的变步长自动搜索算法,以寻找最清晰显微图像,从而完成自动调焦.实验表明:系统可完全取代传统手动调焦操作,且精度更高,在细分驱动条件下,调焦和变倍过程的最小精度可达到1μm.     

All-in-focus imaging using average filter-based relative focus measure

Digital images are normally taken by focusing on an object, resulting in defocused background regions. A popular approach to produce an all-in-focus image without defocused regions is to capture several input images at varying focus settings, and then fuse them into an image using offline image processing software. This paper describes an all-in-focus imaging method that can operate on digital cameras. The proposed method consists of an automatic focus-bracketing algorithm that determines at which focuses to capture images and an image-fusion algorithm that computes a high-quality all-in-focus image. While most previous methods use the focus measure calculated independently for each input image, the proposed method calculates the relative focus measure between a pair of input images. We note that a well-focused region in an image shows better contrast, sharpness, and details than the corresponding region that is defocused in another image. Based on the observation that the average filtered version of a well-focused region in an image shows a higher correlation to the corresponding defocused region in another image than the original well-focused version, a new focus measure is proposed. Experimental results of various sample image sequences show the superiority of the proposed measure in terms of both objective and subjective evaluation and the proposed method allows the user to capture all-in-focus images directly on their digital camera without using offline image processing software.     

基于四元数小波变换的清晰度评价

针对当前各种图像清晰度评价方法在清晰度判别过程中单调性和区分度不够以及适用范围较小的问题,提出了一种基于四元数小波变换（QWT）幅值与相位的图像清晰度评价方法。该算法通过四元数小波变换将图像从空间域变换到频率域,对得到的四元数小波变换系数进一步计算之后获得低频子带与高频子带的幅值与相位信息,求得低频子带幅值各方向的梯度之后与对应方向的相位相乘求和,最终得到两个清晰度指标值。采用该算法与多种现有算法对不同内容的图像、不同程度模糊的图像以及含有不同程度噪声的图像进行清晰度评价实验：相对于现有算法,所提算法在对上述多种图像的清晰度评价中都保持着很好的单调性与区分度。实验结果表明,所提算法不但克服了现有算法在单调性与区分度上的不足,而且所提清晰度评价指标可以应用在图像处理中。     

Blind quality assessment of night-time image

High-quality night-time imaging is crucial to video surveillance, automatic drive and consumer electronics. However, different from day-time imaging, night-time imaging suffers from some disadvantages, such as low light, uneven illumination, difficult focusing, etc., which raises a great concern to the night-time imaging quality. Accordingly, a practical night-time image quality evaluation method is very promising to control and improve the night-time imaging system. Toward this end, in this paper, we propose a blind image quality assessment (BIQA) method to quantify the night-time image quality. Specifically, in the proposed method, we measure the night-time image quality by investigating the fundamental image properties, which are highly relevant to the image quality, such as the brightness, saturation, sharpness, noiseness, contrast and the semantics. Specific features are designed to characterize the image properties properly. Then we employ the support vector regression (SVR) method to infer the image quality with the extracted quality-aware features. The proposed BIQA method for night-time images is thoroughly evaluated on a representative night-time image database. Experimental results demonstrate that the proposed BIQA method for night-time images achieves superior prediction performance to other state-of-the-art BIQA methods.     

Geometric and radiometric evaluation of Razaksat medium-sized aperture camera data

Razaksat, a high-resolution Malaysian remote-sensing satellite, was launched on 14 July 2009. It carries a medium-sized aperture camera (MAC) with one panchromatic and four multispectral bands, of 2.5 and 5 m spatial resolution, respectively. The satellite was placed in a near-equatorial orbit with a low inclination angle of 9° to enable an optimum 14 overpasses per day over the equatorial region (i.e. 9° N to 9° S) as compared to only three daily passes over Malaysia for near-polar orbiting satellites. This article reports on evaluation of the panchromatic and multispectral images of MAC: (i) a geometric evaluation of the panchromatic and multispectral MAC images; (ii) a radiometric evaluation, focusing particularly on the noise level and sharpness of the MAC images; (iii) an evaluation of the MAC panchromatic data for updating planimetric topographic features; and (iv) a classification of MAC multispectral data for land-cover mapping. The noise level within the image set was found to increase with the intensity, while the sharpness of edges tested on the images in all non-homogeneous targets was relatively marginal. However, the outcome of the analysis showed the utility and potential of high-resolution panchromatic and multispectral bands of the Razaksat as stipulated in the system mission for terrain mapping.     

Adaptive regulation of CCD camera for real time eye tracking

In this paper, an eye tracking method and an automatic focusing technique, which combine the regulation of the aperture with the adjustment of the focus of the camera lens, are proposed to acquire clear eye images in the eye-gaze tracking system. Firstly, the aperture of the CCD lens is controlled to adapt the system to external lighting circumstances with the average brightness value of the processed images as the basic value. Secondly, a sum-modulus-difference (SMD) operator is used for rough and quick focusing in a large scale to obtain the eye glints, and for the control of a pan-tilt unit to track and aim at the eye, and for regulation of the lens focus. Finally, a frequency selective weighted median (FSWM) operator is applied in the determined window to focus automatically and acquire clear eye images. If the pupil contour can be extracted from the eye image, then the average gradient value of the pupil’s edge points can be used for real-time focusing. Experimental results show that this system can adapt to external lighting changes and to the user’s head movements. It can track the eye and acquire clear eye images in real-time.     

机器视觉疲劳裂纹扩展试验摄像头自动聚焦方法

在机器视觉疲劳裂纹扩展试验中,为了能够满足对裂纹宏观观察裂纹和准确定位裂纹尖端的要求,需要采用变焦镜头放大和缩小采集图像范围,针对于摄像头变焦后的聚焦问题,提出了摄像头的自动聚焦方法。首先建立图像采集系统,采集裂纹图像至计算机,通过中值滤波对图像预处理,去除噪声干扰,选取裂纹区域作为聚焦窗口,采用Laplace算子法作为清晰度评价函数,并提出一种变步长穷举法进行聚焦搜索。最后设计了以ARM7为核心的摄像头运动控制器。实验表明,所提出的方法能够实现疲劳裂纹扩展试验中摄像头在各种情况下的准确自动聚焦,为下一步精确测量疲劳裂纹扩展参数奠定基础。     

A Robust Speech Recognition System for Communication Robots in Noisy Environments

The application range of communication robots could be widely expanded by the use of automatic speech recognition (ASR) systems with improved robustness for noise and for speakers of different ages. In past researches, several modules have been proposed and evaluated for improving the robustness of ASR systems in noisy environments. However, this performance might be degraded when applied to robots, due to problems caused by distant speech and the robot's own noise. In this paper, we implemented the individual modules in a humanoid robot, and evaluated the ASR performance in a real-world noisy environment for adults' and children's speech. The performance of each module was verified by adding different levels of real environment noise recorded in a cafeteria. Experimental results indicated that our ASR system could achieve over 80% word accuracy in 70-dBA noise. Further evaluation of adult speech recorded in a real noisy environment resulted in 73% word accuracy.