Fast color contrast enhancement method for color night vision

The increasing availability and deployment of imaging sensors operating in multiple spectral bands has led to a large research effort in color image fusion, resulting in a plethora of pixel-level image fusion algorithms. In this study a simple and fast fusion approach for color night vision is presented. The contrast of infrared and visible images is adjusted by local histogram equalization. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To obtain false color images possessing a natural day-time color appearance, this paper adopts an approach which transfers color from the reference to the fused images in a simplified Lab space. To enhance the contrast between the target and the background, a stretch factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot targets are popped out with intense colors while the background details present natural color appearance. Target detection experiments also show that the presented method has a better performance than the former methods, owing to the target recognition area, detection rate, color distance and running time.     

直视型微光夜视系统最小可分辨对比度模型

从信号检测和人眼视觉角度出发,研究了直视微光夜视系统综合性能评估理论,推导出直视型微光成像系统的MRC（最小可分辨对比度）模型。该模型将光学传递特性与系统信噪比结合,建立了系统直视微光夜视MRC与目标特性、直视微光夜视仪以及人眼各部分参数之间的数学关系。验证结果表明,由该模型得到的系统极限分辨率相较于系统实际测出的分辨率相对误差为3.08%。     

Global brightness and local contrast adaptive enhancement for low illumination color image

An adaptive enhancement algorithm is proposed in the paper for low illumination color image which is low brightness and low contrast. The algorithm is realized through three steps: the global brightness adaptive adjustment, locally adaptive contrast enhancement and color restore. Experiments show that the brightness and local contrast of low illumination color image can be effectively enhanced. The details, especially in the dark region of enhanced image are more prominent and the enhanced image is more vivid than some other methods for low illumination color image enhancement.     

Image contrast enhancement using adjacent-blocks-based modification for local histogram equalization

Infrared images usually have some non-ideal characteristics such as weak target-to-background contrast and strong noise. Because of these characteristics, it is necessary to apply the contrast enhancement algorithm to improve the visual quality of infrared images. Histogram equalization (HE) algorithm is a widely used contrast enhancement algorithm due to its effectiveness and simple implementation. But a drawback of HE algorithm is that the local contrast of an image cannot be equally enhanced. Local histogram equalization algorithms are proved to be the effective techniques for local image contrast enhancement. However, over-enhancement of noise and artifacts can be easily found in the local histogram equalization enhanced images. In this paper, a new contrast enhancement technique based on local histogram equalization algorithm is proposed to overcome the drawbacks mentioned above. The input images are segmented into three kinds of overlapped sub-blocks using the gradients of them. To overcome the over-enhancement effect, the histograms of these sub-blocks are then modified by adjacent sub-blocks. We pay more attention to improve the contrast of detail information while the brightness of the flat region in these sub-blocks is well preserved. It will be shown that the proposed algorithm outperforms other related algorithms by enhancing the local contrast without introducing over-enhancement effects and additional noise.     

基于BIRCH聚类加速的彩色图像增强算法

针对现存的大多图像增强算法增强的图像可见性丢失问题,提出了一种基于BIRCH聚类加速的彩色图像增强算法;首先,通过BIRCH聚类加速确定数据库中与输入图像直方图相似度最高的图像来提取图像特征;然后,选择最小欧氏距离的特征值进行图像融合以获取目标图像;最后,增强图像通过目标图像直方图规范化和后期处理获得;大量图像融合实验结果验证了算法的有效性,该算法扩展了图像增强的类别,解决了增强过程中可能出现的可见性丢失问题,使图像增强的适应性更强;另外,EM、CII和SSIM评估指标的结果表明该算法明显改善了增强效果。     

一种可控的视频图像动态对比度增强算法

为增强显示设备进行视频信号显示时的图像对比度,提出了一种幅度可控的动态对比度增强算法。该算法利用一组归一化线性直方图数据和输入图像的归一化灰度直方图数据的结合,实现对输入图像的权重化直方图均衡化处理,进而达到幅度可控的动态对比度增强效果。该算法可以通过控制对比度增强幅度来避免传统直方图均衡化产生的过增强现象。将基于该算法的实时图像处理器应用于50英寸AC PDP上,实验结果表明,其对比度获得显著提升,并且能够根据外部接口的调节实现幅度可控的对比度增强效果。     

夜视领域几个热点技术的进展及分析

作为夜视技术的主要技术途径,微光夜视和红外热成像技术在现代战争中具有重要的地位,掌握先进的夜视技术对于控制战场形势至关重要。随着各种现代夜视技术在世界各国军队中的装备中应用,"拥有黑夜"已逐步成为"共享黑夜"。为继续保持夜视技术的优势,美国及其盟友不断地发展更为先进的夜视技术和装备,并取得重要进展。介绍了夜视技术的几个重要的技术进展,分析了其对整个夜视技术发展以及应用的影响,希望对加快发展我国的夜视技术,促进夜视装备的有效应用起到促进作用。     

微光夜视技术的进展与展望

微光夜视技术作为主要为夜战服务的军用光电子高新技术，其在现代高新技术局部战争和夜战中的作用和地位变得更加突出和重要。随着微光夜视技术的快速发展和器件、系统性能水平的不断提高，微光夜视技术在未来高新技术战争和信息化战争中将具有巨大的发展潜力和广阔的应用前景。在对国外超二代、三代和四代微光像增强器技术发展思路、管型特点和关键技术进行深入分析的基础上，介绍了国内外微光夜视技术的发展现状和最新进展。结合我国目前的设备条件、元器件性能和技术水平的现状，对我国微光夜视技术的发展方向和重要的关键技术进行了阐述，提出了自己的一些建议和展望。     

Perceptual contrast enhancement with dynamic range adjustment

Recent years, although great efforts have been made to improve its performance, few Histogram equalization (HE) methods take human visual perception (HVP) into account explicitly. The human visual system (HVS) is more sensitive to edges than brightness. This paper proposes to take use of this nature intuitively and develops a perceptual contrast enhancement approach with dynamic range adjustment through histogram modification. The use of perceptual contrast connects the image enhancement problem with the HVS. To pre-condition the input image before the HE procedure is implemented, a perceptual contrast map (PCM) is constructed based on the modified Difference of Gaussian (DOG) algorithm. As a result, the contrast of the image is sharpened and high frequency noise is suppressed. A modified Clipped Histogram Equalization (CHE) is also developed which improves visual quality by automatically detecting the dynamic range of the image with improved perceptual contrast. Experimental results show that the new HE algorithm outperforms several state-of-the-art algorithms in improving perceptual contrast and enhancing details. In addition, the new algorithm is simple to implement, making it suitable for real-time applications.     

折反式微光夜视物镜的光学设计

介绍一种长焦距、大相对孔径微光夜视物镜的光学设计。设计参数为焦距100 mm,相对孔径1/1.4,视场10。为增大视距,减小物镜尺寸和质量,并且满足在宽光谱范围消色差的要求,选择均为球面的折反式物镜结构,在相同焦距和相对孔径的条件下折反式系统比折射系统尺寸更小,质量更轻。在设计过程中引入曼金反射镜,增加设计自由度。经优化设计达到较好的成像质量,空间频率在50 lp/mm时,轴上传递函数大于0.4,轴外传递函数大于0.2,与像增强器极限分辨率相匹配,全视场畸变小于2 %,物镜总长达到67 mm。     

基于动态直方图均匀化的对比度增强方法

为增强显示设备进行视频信号显示时的图像对比度,提出了一种动态直方图均匀化算法,该算法根据对比度增强系数可实现在不同灰度范围内的直方图均匀化,达到不同程度的对比度增强效果。同时为减少进行对比度增强所需的帧存储器,开发出了一种快速简单的输入视频图像帧间相似性检测方法及电路实现,当判定输入视频图像具有相似性时,后续帧的图像采用前面输入图像的对比度增强映射函数。仿真结果表明,提出的对比度增强方法能根据对比度增强系数实现不同程度的对比度增强,有效地提高了显示设备的图像显示质量。     

改善光电稳瞄系统视觉效果的图像增强算法

为了改善光电稳瞄系统的视觉效果,使视频图像更加适合于人眼观察,并且有利于对目标的自动跟踪效果,将直方图均衡化处理与拉普拉斯边缘锐化处理相结合,在增强对比度的同时尽量保持边缘细节。仿真结果显示采用本文算法能够有效改善视频图像的视觉效果。     

基于散射介质成像理论的微光夜视系统研究

描述了一种基于大气散射特性分析的微光夜视系统设计。通过分析大气对光学辐射的散射作用,在理想光电成像系统探测方程的基础上,建立了散射介质成像的探测模型,表明大气散射会严重衰减目标对比度,而目标对比度的传递特性即系统调制传递函数将直接影响观察的作用距离。通过选择应用响应光谱主要集中于0.6μm~1.0μm的三代像增强器,优化设计光学系统的MTF,实现了大气环境下的微光系统作用距离的提高。完成的两种焦距分别为250mm和320mm,采用了三代像增强器的夜视仪.野外试验表明,实现对空目标作用距离最大13.7km~18.3km发现、8.0km~8.1km识别。     

微光夜视仪分辨力客观测量方法研究

利用灰度 梯度共生矩阵模型对微光夜视仪分辨力测量图像的纹理特征进行了分析 ,通过对大量图像的 5个纹理特征参数的计算 ,结果表明 ,这些参数能对微光夜视仪分辨力测量图像的纹理特征作出有效的客观评价 ,此计算结果与人眼的观察结果具有较好的一致性。     

Practical considerations in T1 mapping of prostate for dynamic contrast enhancement pharmacokinetic analyses

There are many challenges in developing robust imaging biomarkers that can be reliably applied in a clinical trial setting. In the case of dynamic contrast-enhanced (DCE) MRI, one such challenge is to obtain accurate precontrast T₁ maps for subsequent use in two-compartment pharmacokinetic models commonly used to fit the MR enhancement time courses. In the prostate, a convenient and common approach for this task has been to use the same 3D spoiled gradient-echo sequence used to collect the DCE data, but with variable flip angles (VFAs) to collect data suitable for T₁ mapping prior to contrast injection. However, inhomogeneous radiofrequency conditions within the prostate have been found to adversely affect the accuracy of this technique. Herein we demonstrate the sensitivity of DCE pharmacokinetic parameters to precontrast T₁ values and examine methods to improve the accuracy of T₁ mapping with flip angle-corrected VFA SPGR methods, comparing T₁ maps from such methods with “gold standard” reference T₁ maps generated with saturation recovery experiments performed with fast spin-echo (FSE) sequences.     

Phase contrast enhancement in microscopy using spiral phase filtering

We demonstrate two methods based on Fourier plane filtering using (a) a fractional spiral phase plate (SPP) and (b) an off-axial SPP for phase contrast enhancement in optical microscopy. In comparison to previous works, a spatially incoherent LED is used in the Köhler illumination as the light source to illuminate the biological specimen. We demonstrate that both these methods can transform the phase specimen into a relief-like view even under such illumination. The degree and orientation of enhancement can be controlled by changing the phase structure of the filter. The SPP is displayed on a phase-only spatial light modulator, and can be integrated into the optical path of standard microscopes.     

彩色视觉装置的颜色校正对比实验研究

鉴于利用彩色视觉装置进行在线测量是颜色测量在工业应用发展的趋势,而光源的光谱分布和相机响应函数与人眼的光谱响应曲线的不一致会严重影响测量的精确性,在人工D65光源和LED阵列光源照明下,利用相同的工业相机获取校正图片,采用多项式回归方法在与设备无关空间sRGB和CIEL*a*b*空间进行校正。实验结果显示在校正前平均色差分别为27.68E和16.09E,人工D65光源照明下获取的图片色差较小,校正后不同光源下获取图片的色度趋于一致,分别为2.56E和2.39E。采用sRGB颜色空间,在校正精度、校正步骤、图片显示等方面都要优于CIEL*a*b*空间。以一幅拍摄的实际图片校正为例,显示了色度校正对彩色装置的重要性。     

基于灰度冗余图像融合增强研究

为了改善原图像直方图像素灰度分布集中于低灰度级,与经过常规直方图均衡化处理的图像直方图像素灰度分布集中于高灰度级且均具有灰度冗余的图像增强效果,提出了一种新的图像增强算法.对原始图像进行常规直方图均衡处理,并对原始图像与进行了常规直方图均衡处理的图像分别在尽可能大的范围内进行映射,使两者变换后都尽可能去除灰度冗余而有较大的动态范围.取变换后的两图像各自的优点,融合成一幅效果最好的图像.实验结果验证了理论分析的正确性.     

Color reproduction method by support vector regression for color computer vision

In the color computer vision system, the nonlinearity of the camera and computer screen may result in different colors between the screen and the actual color of objects, which requires for color calibration. In this paper, support vector regression (SVR) method was introduced to reproduce the colors of the nonlinear imaging system. Firstly, successive 3σ method was used to eliminate the large errors found in the color measurement. Then, based on the training set measured in advance, SVR model of RBF kernel was applied to map the nonlinear imaging system. In this step, two important parameters (C, γ) were optimized by the Least Mean Squared Validating Errors algorithm to get the best SVR model. Finally, this optimized model could predict the real values displayed on the screen. Compared with quadratic polynomial regression, BP neural network and relevance vector machine, the optimized SVR model has better ability in color reproduction performance and generalization.