ISAR motion compensation using the burst derivative measure as a focal quality indicator

Inverse synthetic aperture radar (ISAR) is an imaging technique that shows great promise in classifying airborne targets in real-time under all weather conditions. The success of classifying targets using ISAR is predicated upon forming highly focused radar images of these target. Efforts to develop highly focused radar imaging computer software have been challenging, mainly because the imaging depends on and is affected by the motion of the target. Computationally intensive motion compensation algorithms have been developed to remove the unwanted degrading effects of target motion. Those particular motion compensation algorithms which require the use of a space domain focal quality indicator (e.g., entropy) to determine image sharpness as processing proceeds pay a severe computational penalty due to the large number of two-dimensional fast Fourier transforms (2D-FFTs) which must be computed. This is due to the fact that the actual processing of ISAR data is done primarily in the spatial frequency domain and not in the space domain where the final ISAR image is displayed. If a focal quality indicator could be developed to measure image sharpness in the spatial frequency domain, then the computational burden introduced by the numerous 2D-FFTs could be greatly relaxed. This article describes the use of a new focal quality indicator called the burst derivative measure for determining ISAR image sharpness in the spatial frequency domain. Tests have been performed on simulated as well as actual ISAR data using both the burst derivative measure and the entropy measure. Results indicate that the burst derivative measure, when used in conjunction with the entropy measure, can greatly reduce the number of 2D-FFTS presently required in these motion compensation algorithms.©1993 John Wiley & Sons Inc     

Clinical image quality criteria for full field digital mammography: a first practical application

In order to quantify the clinical quality of full-field digital mammography, a set of image quality parameters is developed. The set consisted of 12 image quality criteria and 8 physical characteristics of the image. The first set interrogates the visibility of anatomical structures and typical characteristics of a digital image, such as noise and saturation of dark and white areas. The second set of criteria evaluates contrast, sharpness and confidence with the representation of masses, microcalcifications and the image. The use of these criteria is reported in a retrospective study, in which the impact of dose on the radiological quality of digital mammograms is evaluated. Fifty patients acquired in a low-dose mode were retrieved and compared with 50 patients acquired in a dose mode that was set 41% higher. The dose affects, more than expected, contrast and sharpness of the image, whereas the visibility of the anatomical structures remains unchanged. With these parameters, quantification of the image quality is possible; however, because of subjectivity of the parameters, only intra-observer comparison and evaluation of the individual parameters rather than the overall results are advised. Together with physical tests of image quality, critical radiological evaluation of the quality should be included in the acceptance process of digital mammography.     

Aberration correction by maximizing generalized sharpness metrics

The technique of maximizing sharpness metrics has been used to estimate and compensate for aberrations with adaptive optics, to correct phase errors in synthetic-aperture radar, and to restore images. The largest class of sharpness metrics is the sum over a nonlinear point transformation of the image intensity. How the second derivative of the point nonlinearity varies with image intensity determines the effects of various metrics on the imagery. Some metrics emphasize making shadows darker, and other emphasize making bright points brighter. One can determine the image content needed to pick the best metric by computing the statistics of the image autocorrelation or of the Fourier magnitude, either of which is independent of the phase error. Computationally efficient, closed-form expressions for the gradient make possible efficient search algorithms to maximize sharpness.     

结合复小波域和空间总变分的无参考图像清晰度评价

目的针对频域和空域相结合的清晰度评价方法耗时太长、与主观评价一致性不高等问题,提出结合复小波域和空间总变分的感知清晰度评价方法。方法采用低通滤波的方法将原始图像再模糊,得到其参考图像;在复小波域上采用局部相位一致性计算原始图像和参考图像的清晰度图,在空间域上采用总变分计算原始图像和参考图像的清晰度图;分别将原始图像以及参考图像各自的2幅清晰度图进行几何加权平均,得到2幅整体的感知清晰度图;计算2幅感知清晰度图的相似性,得到原始图像的感知清晰度值。结果在LIVE数据库上的SROCC值达到0.9476,CC值达到0.9483,一幅测试图所耗时间为6.003 s。结论实验证明文中算法的评价性能较优,相较同样结合频域和空域的评价方法计算复杂度降低,耗时较少,更加符合人眼视觉主观感知清晰度。     

区域曝光与曝光控制应用技巧

本文从安塞尔.亚当斯的区域曝光法与当代摄影常用胶片的感光特性曲线的联系着手,全面地阐述了在拍摄过程中,如何通过曝光控制和根据胶片的画幅,选择适宜的后期制作程序,获得具有丰富的影调层次、较高的清晰度、良好的颗粒性和质感强烈的优秀摄影作品的方法。     

Signal-to-noise ratio for temporal integrated drifting images: a model for perceived image sharpening

A formulation of signal-to-noise ratio is constructed that uses temporal integrated images from image sequences. Given a blurred image that drifts horizontally at various speeds and at various linear blurs, we prove that this formulation of the signal-to-noise ratio consistently increases with an increase in speed. This increase is shown to model the trends in the human vision system by which drifting blurred images are perceived with increased sharpness. The existing widely used objective quality techniques fail to model the perceptual increase in sharpness. This new formulation, along with other objective quality measures, is tested on several blurred drifting image sequences. The new formulation reflects the theoretically predicted increase in perceived sharpness.     

一种内容时变的显微细胞图像清晰度度量方法

清晰度度量对于细胞扫描系统具有重要的意义.对于同一内容的图像,清晰图像的边缘相对模糊图像具有较大的灰度变化率的特征.对于内容时变的图像,运用图像灰度梯度方法来度量清晰度并不适用.本文提出了一种内容时变的显微图像的清晰度度量方法.通过实验验证,该方法速度快,计算量小,可靠性高.     

基于空间频率响应的印刷品清晰度检测

利用CCD 图像捕获设备,把印刷测试图转换为数字图像,采用基于倾斜边缘梯度分析的空间频率响应检测算法,测量获得了印刷复制系统的空间频率响应特性,并把经过人眼视觉系统滤波后得到的空间频率响应曲线内的面积作归一化处理后,所获得的测量值作为清晰度质量描述因子。实验结果表明,清晰度质量描述因子能较好地反映印刷品的清晰度复制质量,提供了一种新的客观、定量检测印刷品清晰度的方法,为实现印刷品质量的自动化检测与评价提供了有力的技术支持。     

影响刑事照相清晰度的因素及对策

本文指出刑事照相清晰度受照明、镜头、机振、手振、感光胶片等因素的影响．并指出了提高清晰度的措施。     

Perceptual denoising of color images

Denoising of color images is a trade‐off between sharpness of an image and perceived noise. We formulate a novel optimization problem that can maximize sharpness of an image while limiting the perceived noise under a model of visibility of additive random noise. We derive a closed‐form expression for an optimal two‐dimensional finite impulse response filter, show its uniqueness and existence, and present simulation results for black and white as well as color images. Simulation results show remarkable reduction in perceptibility of noise, while preserving sharpness. The computational burden required for the optimal filter is reduced by a new adhoc filter which is simple but has near optimal performance. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 215–222, 2010.     

卫星数字化影像输出技术及其应用效果

随着数码成像技术的发展，卫星影像图制作过程中由于光学镜头产生的几何畸变，图像边缘模糊等图像失真问题得到根本解决，可显著提高卫星图像的清晰度和几何精度；而美国圣保利克公司生产的Light-Jet-5000RS型激光数码成像仪是目前国际上图像精度最高的图像输出设备，可获得较满意的卫星图像，本文扼要介绍了其成像原理，技术参数和实际应用效果。     

基于图像清晰度评价的摄像头辅助调焦系统

提出一种新的图像清晰度(包括锐度和对比度)评价函数,对比传统的图像清晰度评价算法,新算法速度最快且准确,以及和功率谱算法一样优良的灵敏度,适合各种实时自动对焦系统.本文使用一系列不同程度的离焦图片演示了所有算法的性能。同时将新算法应用于一种实际的摄像头模块辅助调焦系统中,系统把采集的每帧图像实时显示在屏幕上,用新算法评价图像的清晰度,从而指导作业员对摄像头模块进行调焦。实践表明该摄像头辅助调焦系统在批量生产摄像头模块时对提高生产效率和稳定质量方面有很大作用。     

Calculation and correction of subaperture tilt aberration modes in synthesis imaging

We extend the redundant spacings calibration method for finding piston coefficients affecting the elements of a dilute aperture array so that tilt phase coefficients can also be calculated and corrected without the need for assumptions about the object. The tilt coefficient retrieval method is successfully demonstrated in simulation, and the specifics of correction by image sharpness are discussed, showing that in dilute aperture systems this method does not necessarily produce a unique image.     

网点形状对图像复制质量影响的实验研究

网点形状是影响印刷图像复制质量的因素之一,在一定的实验条件下,将标准彩色图像数据N1~N8作为测试图像,进行了圆形、椭圆形、方形、方圆形网点的输出。对图像的阶调层次、清晰度、色彩、灰平衡等进行了主观评价,统计并分析了评价结果。实验表明:圆形网点在高调层次、清晰度、色彩方面的复制效果最好;椭圆形及方圆形网点在中暗调层次复制方面表现最好。     

Hardness variation with indenter sharpness in an Au thin-film

The effects of the indenter shape on hardness were studied from thin-film nanoindentations. Two Berkovich indenters with different operating histories were prepared and their morphologies were measured with an atomic force microscope. The curvature radii of both indenters that were measured through an image analysis were 58.8 nm and 732.2 nm, respectively. The nanoindentations were carried out on a 1.2 microm-thick Au thin-film with a Nanoindenter XP system with both indenters. Various nanoindentation data with indenter exchanges were surveyed, and they showed that the peak indentation loads under the blunter indenter were higher than those of the sharper indenter at the same indentation depths. The indenter sharpness parameter was used to correct the raw nanoindentation curves. The corrected curves overlapped well and the resulting hardness values were consistent regardless of the indenter sharpness. The intrinsic hardness values of the Au thin-film from both indenters agreed with each other, with only a 0.6% difference. This means the indenter sharpness was properly corrected and that the sharpness must be considered when the contact properties are measured at shallow indentations.     

General Image-Quality Equation: GIQE

A regression-based model was developed relating aerial image quality, expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS), to fundamental image attributes. The General Image-Quality Equation (GIQE) treats three main attributes: scale, expressed as the ground-sampled distance; sharpness, measured from the system modulation transfer function; and the signal-to-noise ratio. The GIQE can be applied to any visible sensor and predicts NIIRS ratings with a standard error of 0.3 NIIRS. The image attributes treated by the GIQE are influenced by system design and operation parameters. The GIQE allows system designers and operators to perform trade-offs for the optimization of image quality.     

An automatic focusing algorithm

A simple and effective automatic focusing algorithm is proposed in this article. The principle of the proposed automatic focusing algorithm is based on that, for the radial test pattern, a best‐focused image should have the smallest blurred region in the middle of the acquired image, and hence, should have the smallest equivalent radius. The circular Hough transform has became a common method in numerous image‐processing applications for circle detection. Various modifications to the basic circular Hough transform have been suggested, such as: the inclusion of edge orientation, simultaneous consideration of a range of circle radii, the use of a complex accumulator array with the phase proportional to the log of the radius, or for filter operations. The purpose of this work is to show that a radius of a circular region extracted by a normalized circular Hough transform is a possible solution for determining the sharpness of images. To acquire high quality images with a given CCD camera, it is crucial that the camera be located exactly at the back length of the lens, i.e., the focus position of the lens. In the best conditions, the contours of the acquired images are of the sharpest, with none of the blurring effects associated with unfocused images. Acquiring such high quality images by these means is the main goal of the automatic focusing algorithm proposed in this article. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 12, 235–238, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10029     

Estimation of perceived image blur using edge features

Sharpness (or its complement, perceived blur or unsharpness) is an important attribute of image quality, and the spread of the physical blurring kernel is the predominant parameter determining that attribute. In this article we present an algorithm to estimate an objective measure for sharpness, called the blur index. The algorithm first estimates the physical parameter of blur spread from the blurred image and subsequently uses that estimate to compute the blur index. A global estimate of blur spread for the entire image is obtained by the weighted averaging of the local estimates of blur spread at prominent edge locations in the image. These local estimates at edges are obtained by nonlinearly combining local derivatives. The edge prominence is based on the edge height and the edge-contour length. The blur index is computed from the estimated blur spread by taking the sensitivity of the visual system to changes in the blur spread into account. The results of a psychophysical experiment in which subjects judged the unsharpness of natural images are also reported. By correlating the estimates of the blur index, as obtained from the algorithm, with the results obtained in the psychophysical experiment, we show that the blur index correlates well with the perceived unsharpness, and hence can be considered a psychometric measure of sharpness. © 1996 John Wiley & Sons, Inc.     

彩色负片染料型黄滤色层

黄滤色层是确保彩色底片彩色还原真实和提高影像清晰度的一项重要组分。黄滤色层可由胶态金属银或特定的黄色染料构成，也可由两者组合而成。本文扼要介绍了各类黄滤色层的性能特点，并对其优缺点进行了比较。     

Investigation into the Quality of the Kinematographic Image

In a previous series of papers the results were published which the authors obtained in their investigation into different aspects of the problem of quality of the kinematographic image. The present paper considers this problem as a whole.

In evaluating the quality of the kinematographic image the following criteria are used: tone rendering, image sharpness, resolution in small-size details, and graininess. These criteria cannot give full evaluation of image quality. as the latter depends, to a considerable extent, on other conditions which determine its emotional effect. In other words, satisfactory values for the above listed quantitative criteria are a necessary but not a sufficient condition for obtaining high quality kinematographic images. In addition, the image should be evaluated as visually good.

The investigation is confined to the above four quality criteria, assuming that the problem, so for as kinema engineering is concerned. is that of obtaining a high quality imafe in the technial meaning of the term, i.e.. an image transmitting the maximum perceptible amount 0 information on the subject. The realization of these possibilities by the producer, cameraman, actor, etc., is not considered.

The values of quality criteria for any of the successive stages of kinematographic images fmaster negative, Intermediate positive, duplicating film. screen positive) should be based first on a precise knowledge of their contribution to the screen image, and secondly-on the lows correlating their values on the screen with those in preceding images.