Transfer color to night vision images

Natural color appearance is the key problem of color night vision field. In this paper, the color mood of daytime color image is transferred to the monochromic night vision image. This method gives the night image a natural color appearance. For each pixel in the night vision image, the best matching pixel in the color image is found based on texture similarity measure. Entropy, energy, contrast, homogeneity, and correlation features based on co-occurrence matrix are combined as texture similarity measure to find the corresponding pixels between the two images. We use a genetic algorithm (GA) to find the optimistic weighting factors assigned to the five different features. GA is also employed in searching the matching pixels to make the color transfer algorithm faster. When the best matching pixel in the color image is found, the chromaticity values are transferred to the corresponding pixel of the night vision image. The experiment results demonstrate the efficiency of this natural color transfer technique.     

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.     

微光彩色夜视光学系统设计与像质评价

为了充分利用可见光和长波红外所蕴含的不同信息进行数据融合、彩色显示,分析了3种不同类型双波段光学系统及其成像性能,设计了全折射光学系统、折反射光学系统和离轴三反射双谱光学系统。采用不同的分光形式,反射可见光波段,透射长波红外波段,使3种不同类型光学系统的全视场角和相对孔径分别为5°和1∶1.7;光学系统在可见光波段成像质量对应的空间频率50 lp/mm处的MTF=0.60,在长波红外波段成像质量对应的空间频率15 lp/mm处的MTF=0.30。对不同结构类型的系统特点进行分析和讨论,给出了各种像差曲线和光学传递函数曲线,为多波段彩色夜视设计了不同类型的光学系统。     

Kernel based color estimation for night vision imagery

Displaying night vision (NV) imagery with colors can largely improve observer's performance of scene recognition and situational awareness comparing to the conventional monochrome representation. However, estimating colors for single-band NV imagery has two challenges: deriving an appropriate color mapping model and extracting sufficient image features required by the model. To address these, a kernel based regression model and a set of multi-scale image features are used here. The proposed method can automatically render single-band NV imagery with natural colors, even when it has abnormal luminance distribution and lacks identifiable details.     

Effective contrast enhancement method for color night vision

Image fusion refers to the techniques that integrate complementary information from multiple image sensors’ data in a way that makes the new images more suitable for human visual perception. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Firstly, the contrast of infrared and visible images is enhanced using local histogram equalization and median filter. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To enhance the color contrast between the target and the background, the scaling factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot and cold targets are all popped out with intense colors while the background details present natural color appearance. Target detection experiments through target recognition area, detection rate, target-background discrimination also show that the presented method has a better performance than the former methods.     

三波段微光彩色夜视方法研究

为克服夜视设备产生单色图像的缺陷,得到更符合人眼视觉的彩色夜视图像。根据RGB理论模型以及滤光片的分谱作用原理,基于第二代像增强器设计出一种彩色夜视方案,通过测量滤光片的光谱透过率,得出滤光片对像增强器信噪比的影响;提出利用全波图像的四帧融合解决像增强器信噪比低的问题,并进行实验验证。实验结果显示室内和室外情况下四帧融合彩色图像熵和方差分别达到6.8、35.39及7.0、45.07,均优于三帧融合时对应值,说明提出的四帧融合方法能够克服信噪比降低的缺陷,得到清晰且信息量丰富的夜视图像。     

Design of a color coded target for vision measurements

As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this study, a novel color coded target is designed for vision measurements. A reference position is defined to avoid the repeated coding as well as simplify the coding structure, and a pair of concentric circles is utilized for the precise location of the target. An edge-based identification and location algorithm is proposed for the designed coded target. In this algorithm, a coarse-fine strategy is employed to improve the efficiency and various judgments are made to ensure the correctness of the identification. No human involvement is required except for the adjustment of thresholds in the beginning, which is conducive to the automation of measurement. The algorithm shows high accuracy and robustness in experiments.     

Testing color difference evaluation methods for color digital images

A psychophysical experiment is carried out to evaluate the color difference between pairs of color digital images and their modulated versions, which are displayed on a professional liquid crystal display (LCD) monitor, using the category judgment method. The modulated images for six original images are generated with variations in five attributes, namely, lightness, chroma, hue, resolution, and sharpness, considering both their chromatic and spatial characteristics. Several color difference evaluation methods, namely, CIELAB, CIEDE2 000, CAM02-UCS, S-CIELAB, and iCAM, are compared based on the experimental data. The results demonstrate that the performance of iCAM is the best for predicting image color difference.     

基于深度学习的无人车夜视图像语义分割

为了增强无人车对夜视图像的场景理解,在夜间模式下更快更精确地探测和识别周围环境,将深度学习应用于夜视图像的场景语义分割,提出了一种基于卷积-反卷积神经网络的无人车夜视图像语义分割方法。在传统的卷积神经网络中加入反卷积网络,构建卷积-反卷积神经网络,无需手工选取特征。通过像素到像素的学习和训练,得到图像语义分割模型,可直接用该模型预测夜视图像中每个像素所属的场景语义类别,实现无人车夜间行驶时的环境感知。实验结果表明,该方法具有较好的准确性和实时性,平均IU达到68.47。     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

Review of night vision technology

Night vision based on technology of image intensifier tubes is the oldest electro-optical surveillance technology. However, it receives much less attention from international scientific community than thermal imagers or visible/NIR imagers due to series of reasons. This paper presents a review of a modern night vision technology and can help readers to understand sophisticated situation on the international night vision market.     

A united optimum images fusion based on analysis of color distortion

In remote sensing community, IHS (intensity, hue, and saturation) transform is one of the most commonly used fusion algorithm. A study on IHS fusion indicates that the color distortion cannot be avoided.Meanwhile, wavelet decomposition has a property of frequency division in transform domain. And the statistical property of wavelet coefficient reflects those significant features. So, a united optimal fusion method, which using the statistical property of wavelet decomposition and IHS transform on pixel and feature levels, is proposed. That is, the high frequency of intensity component I is fused on feature level with multi-resolution wavelet in IHS space, and the low frequency of intensity component I is fused on pixel level with optimal weight coefficients. Spectral information and spatial resolution are two performance indexes of optimal weight coefficients. Experiment results show that it is a practical and effective method.     

红外和彩色可见光图像亮度-对比度传递融合算法

以红外和彩色可见光图像为研究对象,提出了一种基于亮度-对比度传递（LCT）技术的彩色图像融合算法。首先借助灰度融合方法将红外图像与彩色可见光图像亮度分量融合,然后用LCT技术改善灰度融合结果的亮度和对比度,最后利用快速YCBCR变换融合策略在RGB空间内直接生成彩色融合图像。文中利用像素平均融合法和多分辨率融合法作为不同的灰度融合措施以分别满足高实时性和高融合质量的需求。实验结果表明,提出算法的融合结果不仅具有与输入彩色可见光图像相近的自然色彩,而且具备令人满意的亮度和对比度,即使采用运算简单的像素平均法进行灰度融合,同样可以获得良好的融合效果。     

Feature-based fusion of infrared and visible dynamic images using target detection

We employ the target detection to improve the performance of the feature-based fusion of infrared and visible dynamic images, which forms a novel fusion scheme. First, the target detection is used to segment the source image sequences into target and background regions. Then, the dual-tree complex wavelet transform (DT-CWT) is proposed to decompose all the source image sequences. Different fusion rules are applied respectively in target and background regions to preserve the target information as much as possible. Real world infrared and visible image sequences are used to validate the performance of the proposed novel scheme. Compared with the previous fusion approaches of image sequences, the improvements of shift invariance, temporal stability and consistency, and computation cost are all ensured.     

Quality assessment for visible and infrared color fusion images of typical scenes

Two comprehensive evaluation metrics, image perceptual quality based on target detectability (PQTD) and perceptual quality based on scene understanding (PQSU), are proposed to measure image quality for visible and infrared color fusion images of typical scenes. A psychophysical experiment is performed to explore the relationship between conventional quality attributes and the proposed evaluation metrics. The prediction models for PQTD and PQSU are derived by multiple linear regression statistical analyses. Results show that the variation of PQTD can be predicted by sharpness and perceptual contrast between the target and background, and that color harmony and sharpness can predict PQSU. The proposed evaluation metrics and their prediction models provide a foundation for further developing objective quality evaluation of color fusion images.     

低照度条件下三基色获取及真彩色融合方法研究

鉴于低照度条件下彩色成像都是采用微光、红外、紫外等波段图像融合成假彩色,提出一种利用滤光片过滤和像增强器增强的三基色获取及真彩色融合方法。采用F P滤光片设计出了透射中心在三基色光中心波长的三基色滤光片,对其光谱透过性进行分析;通过旋转三基色滤色轮将目标反射光过滤,使用像增强器对过滤后反射光增强,借助FPGA编写的控制程序实现滤色轮转速和CCD摄像机成像时间的精确同步,利用CCD摄像机获取经增强后的三基色图像,实现目标三基色图像的动态采集。研制的样机在微光实验室进行了三基色采集及融合实验,实验时光照度分别1×10-1 lx （等效于月光下）和1×10-3 lx（等效于星光下）,采集速度设置为60 f/s,对获取的图像质量进行了评价。结果表明:在照度为1×10-1 lx时,融合后的真彩色图像在灰度均值、灰度方差和信息熵3项指标方面,比3幅单色图像的平均值分别提高了5.06%、5.97%和1.08%;在照度为1×10-3 lx时,融合后的真彩色图像与3幅单色图像的平均值分别提高了13.18%、-9.86和8.65%。     

基于Land实验的可见红外伪彩色图像融合方法

由Land在研究人类视觉颜色恒定性现象时从所做的某个实验出发,通过对该实验中所用红、绿色滤波片的理想化假设以及光源的等能分布假设,并建立红外图像与红色透明片、可见光图像与绿色透明片的对应关系,得到Land实验启发下的新的伪彩色融合算法。通过与Toet伪彩色融合算法的结果比较,说明了该方法的有效性。进而借鉴Toet算法中强调图像特有成分的思想,使本算法输出更丰富、更逼近真实景物的色彩。     

Color fusion of SAR and FLIR images using a natural color transfer technique

Fusion of synthetic aperture radar (SAR) and forward looking infrared (FLIR) images is an important subject for aerospace and sensor surveillance. This paper presents a scheme to achieve a natural color image based on the contours feature of SAR and the target region feature of FLIR so that the overall scene recognition and situational awareness can be improved. The SAR and FLIR images are first decomposed into steerable pyramids, and the contour maps in the SAR image and the region maps in the FLIR image are calculated. The contour and region features are fused at each level of the steerable pyramids. A color image is then formed by transferring daytime color to the monochromic image by using the natural color transfer technique. Experimental results show that the proposed method is effective in providing a color fusion of SAR and FLIR images.     

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。     

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。