基于距离选通的水下偏振光成像系统的研究

光在水下传输受到吸收和散射的影响,限制了水下成像的成像距离和成像清晰度。为能抑制后向散射光的干扰,结合距离选通技术和偏振成像技术的各自的特点,提出了基于距离选通的偏振成像方式。基于距离选通的偏振成像一方面利用同步控制装置,时间上分离目标反射光,另一方面通过水体散射光和物体散射光解偏振度的差异来实现成像。本文分析了基于距离选通的偏振成像原理,具体给出了实验装置和实验过程。通过实验分析,得出基于距离选通的偏振成像技术运用于水下成像的可行性,且能大大提高图像的对比度,使其成像质量优于距离选通方式。     

一种基于Freeman分解与散射熵的极化SAR图像迭代分类方法

该文提出了一种基于Freeman分解与散射熵的极化SAR图像迭代分类新方法.该方法首先通过Freeman分解提取3种散射机理成分的功率,同时通过H/分解提取地物的散射熵;再利用这4个表征地物特性的参数将极化SAR图像中的地物划分为9个初始类,最后使用Wishart分类器对初始类进行迭代分类得到最终的结果.该方法合理利用了地物的极化散射信息,能够取得较好的分类效果,同时运算量也比较小.实测极化SAR数据的实验结果验证了该方法的有效性.     

UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation

Unmanned aerial vehicle (UAV) remote imaging is affected by the bad weather, and the obtained images have the disadvantages of low contrast, complex texture and blurring. In this paper, we propose a blind deconvolution model based on multiple scattering atmosphere point spread function (APSF) estimation to recovery the remote sensing image. According to Narasimhan analytical theory, a new multiple scattering restoration model is established based on the improved dichromatic model. Then using the L0 norm sparse priors of gradient and dark channel to estimate APSF blur kernel, the fast Fourier transform is used to recover the original clear image by Wiener filtering. By comparing with other state-of-the-art methods, the proposed method can correctly estimate blur kernel, effectively remove the atmospheric degradation phenomena, preserve image detail information and increase the quality evaluation indexes.     

动态大气散射系数的颜色衰减先验图像去雾

针对颜色衰减先验图像去雾算法存在对较浓的有雾图像去雾效果不佳的问题,提出基于动态大气散射系数的颜色衰减先验图像去雾算法.用动态大气散射系数取代颜色衰减先验去雾算法中恒定大气散射系数的假设,定义大气散射系数为关于图像景深的指数函数.利用Middlebury stereo datasets中无雾图像和相应的景深图像得到合成有雾图像.采用均方误差(MSE)和结构相似度(SSIM)的综合评价参数MSE-SSIM确定上述指数函数的两个参数的最佳取值.实验结果表明与颜色衰减先验算法、He、Meng算法相比,该算法的去雾图像清晰颜色自然,有效地提高了去雾效果.     

基于暗原色先验模型的水下彩色图像增强算法

针对在水下环境中,光的散射和衰减导致水下光学成像质量严重下降,图像对比度低、颜色失真的问题,提出了一种暗原色先验和基于通道直方图量化的颜色校正算法相结合的图像增强新方法。对于待增强的水下彩色图像,首先建立水下光学图像成像模型,并利用优化与改进的暗原色先验算法对图像进行去模糊,然后通过分析R、G、B三通道的累积直方图,对去模糊后的彩色图像各通道灰度值进行量化,实现图像的颜色校正。实验结果表明,提出的方法可以有效地消除了由于光的散射造成图像的模糊,有效提高了水下图像的视觉效果,恢复水下图像的颜色平衡。     

Scattering-model-based speckle filtering of polarimetric SAR data

A new concept in polarimetric synthetic aperture radar (POLSAR) speckle filtering that preserves the dominant scattering mechanism of each pixel is proposed in this paper. The basic principle is to select pixels of the same scattering characteristics to be included in the filtering process. To achieve this, the algorithm first applies the Freeman and Durden decomposition to separate pixels into three dominant scattering categories: surface, double bounce, and volume, and then unsupervised classification is applied. Speckle filtering is performed using the classification map as a mask. A single-look or multilook pixel centered in a 9 /spl times/ 9 window is filtered by including only pixels in the same and two neighboring classes from the same scattering category. This filter is effective in speckle reduction, while perfectly preserving strong point target signatures, and retains edges, linear, and curved features in the POLSAR data. The effect of speckle filtering on scattering characteristics, such as entropy, anisotropy, and alpha angle, will be discussed.     

基于物理模型的快速单幅图像去雾方法

在雾天环境下,获取的图像受到大气粒子散射的影响而导致对比度和能见度降低.针对该问题,提出了一种基于物理模型的单幅图像的快速去雾方法.该方法以大气散射模型为基础,引入暗原色先验规律求取全局大气光,利用双边滤波局部估计雾浓度,间接求取大气耗散函数,最终通过变换的大气散射模型恢复无雾图像.大量实验结果表明,该方法能够恢复出自然清晰的无雾图像,并能够较好地处理景深突变的边缘及远景处.此外,该算法在处理图像的运算时间上具有明显的优势,可满足图像实时处理要求.     

分形粗糙面上方目标电磁散射特性的研究

利用分形函数来模拟海地粗糙表面，在考虑到粗糙面的粗糙度，入射波极化方式以及粗糙面的动态和静态等因素对电磁散射特性影响的情况下，运用克希霍夫近拟条件，对粗糙面上方平板目标电磁散射的物理机制进行了分析和研究。理论分析和数值结果表明，本文所述方法物理图象清晰，是一种有效分析实际粗糙面与目标相互作用的方法。     

基于去取向理论的全极化SAR图像非监督分类

由于复杂地表目标的取向往往是随机分布的,产生散射回波的随机起伏使散射目标分类不容易明确,采用常规的分类方法容易造成地表的分类混淆.文中提出了一种全极化SAR图像非监督分类方法,首先对数据进行极化去取向处理,提取极化特征参数u、v,结合极化熵参数H进行非监督分类;之后将分类结果作为改进C-均值算法的初始类别划分,基于由u/v/H3个参数组成的特征空间,采用迭代方法实现对地物的分类;最后对NASA/JPL实验室的实测数据进行了实验分析,验证了文中所提分类方法的有效性.     

改进的伽马校正与多尺度融合的水下图像增强

由于光在水下传播会发生吸收和散射,导致采集 的水下图像出现模糊、对比度低、色偏、光照不 均匀等问题。针对以上问题,提出了一种改进的伽马校正与多尺度融合的水下图像增强算法 。首先基于G 通道对R和B通道进行补偿,并对RGB 三通道进行直方图拉伸后使用灰度世界(Gray World) 算法得到颜 色校正图像;然后使用改进的伽马函数改善颜色校正后图像光照不均匀问题,得到光照均匀 图像,并进 行归一化处理;再对光照均匀图像使用限制对比度的自适应直方图均衡化(contrast limite d adaptive histogram equalization,CLAHE)算法得到对比度提升图像;最后采用多尺度融 合算法对以上得出的3幅图 片进行融合,得出增强图像。实验结果表明,提出的算法对不同水下环境的图像均有较好的处理 效果,图像质量评价指标得到明显提高。     

3-D color histogram equalization by principal component analysis

Color histogram equalization is a method for improving visual appearance of images by enhancing image contrast. Color histogram equalization methods are mostly faced with problems like over-enhancement and brightening. In this paper a new color histogram equalization method is proposed which defines a new three dimensional cumulative distribution function based on a one-dimensional histogram. This one-dimensional histogram is calculated by taking into account the correlation between color channels using PCA. Over-enhancement and brightening are solved by this method because of applying the equalization on a transformed image instead of image itself.     

A canonical problem in electromagnetic backscattering from buildings

In this paper, a geometric and electromagnetic model of a typical element of urban structure is presented, in order to analytically evaluate in closed form its electromagnetic return to an active microwave sensor. This model can be used to understand what information on geometric and dielectric properties of a building can be extracted from microwave remote sensing data. The geometrical model consists of a rectangular parallelepiped whose vertical walls form a generic angle with respect to the sensor line of flight. The parallelepiped is placed on a rough surface. The radar return from such a structure can be decomposed into single-scattering contributions from the (rough) ground, the building roof (a plane surface in our model), and vertical walls and multiple scattering contributions from dihedral structures formed by vertical walls and ground. In our model, single-scattering contributions are evaluated by using either physical optics (PO) or geometrical optics (GO), depending on surface roughness. In order to account for multiple scattering between buildings and terrain, we use GO to evaluate the field reflected by the smooth wall toward the ground (first bounce) or the sensor (second or third bounce) and GO or PO (according to ground surface roughness) to evaluate the field scattered by the ground toward the wall (first or second bounce) or the sensor (second bounce). Finally, the above model is used to analyze the field backscattered from a building as a function of the main scene parameters; in particular, the angle between vertical walls and sensor line of night and the dependence on the look angle are analyzed.     

基于融合策略的单幅图像去雾算法

为了有效增强雾天衰退图像,提出了一种基于融合策略的单幅图像去雾算法。该融合策略无需依靠大气散射模型或场景结构信息,只需通过原始衰退图像来获取其输入图与权重图。其中2幅输入图的作用主要是对原有雾图像进行颜色校正和对比度增强,而3幅权重图则突显了图像雾气较浓区域的细节信息。融合策略将上述输入图与权重图相融合以生成对比度高、色彩丰富的去雾图像。此外,本文还从人类视觉感知的角度提出了一个新的去雾效果评价指标,从而为图像去雾与去雾效果评价问题提供了新的解决思路。实验结果表明,与已有方法相比,提出的基于融合策略的去雾算法能更好地提高各种雾天图像的清晰度。     

一种SAR与可见光图像压缩感知融合增强方法

针对机载多传感器成像战场态势感知的问题，提出了一种合成孔径雷达(Synthetic Aperture Radar，SAR)与可见光图像压缩感知融合增强方法。该方法首先对SAR与可见光图像分别进行压缩感知测量，得到压缩测量值，然后通过基于局部权值的融合方法实现对压缩测量值的融合，再利用有序度最优分割法提取SAR图像的强散射目标，最后对融合测量值重建得到初步融合图像，初步融合图像通过目标对比度增强得到最终融合图像。对多组图像进行了仿真分析，视觉及数值结果表明该方法能显著增强融合图像的目标对比度，提升了图像纹理清晰度，较大程度降低了图像融合过程中的数据计算量。     

A novel haze image steganography method via cover-source switching

In realistic outdoor scenarios, image sensors tend to suffer from various weather conditions (e.g., haze, rain, etc.),which make the images of the same scene taken at different times may be different. Therefore, one should be able to securely embed secret messages into these images by making use of the variations of the weather effects. Inspired by some recent natural steganography algorithms, this paper presents a novel haze image steganography method, which embeds messages through adjusting the weather effects of an input haze image, making it resemble the same image captured under another weather condition. The proposed steganography method consists of three parts: (1) model parameter estimation of the input haze image, (2) haze effects adjustment according to the atmospheric scattering model, (3) message embedding using the floating-point adjusted haze image. 10,000 haze images captured under different haze conditions in various scenarios were used to test the proposed steganography algorithm. The experimental results show that the proposed steganography algorithm is more secure than S-UNIWARD and HILL for steganalyzers who only have raw haze images.     

Statistical scattering model in urban propagation environment

A statistical scattering model for mobile radio channels that has the following three features is proposed: 1) the effective scattering area (ESA) is expressed by an ellipse, the center of which is the mobile station (MS) location; 2) the major axis of the ellipse runs parallel along the street where the MS is located; and 3) the scattering power density function around the MS is expressed by a combination of two Laplacian distributions in which the standard deviations are different. To verify the proposed model and obtain realistic values for the model parameters, the spatiotemporal path data observed at a base station (BS) were measured using a 2.2-GHz band in a macrocell scenario (BS antenna height is 60 m) in a typical urban area. The scattering positions are detected from the path information such as the azimuth arrival angle and path length, assuming a single bounce. The spatial distribution of the scattering power is analyzed using principal component analysis. The results showed the ESA to be the anticipated ellipse with the major and minor axes of approximately 210 and 120 m, respectively (axis ratio: approximately 1.7). Furthermore, the power profiles that are projected for each axis of the ellipse can be approximated as Laplacian distributions. Finally, simplification of the proposed model is discussed.     

一种基于红外对比度提升的高动态范围压缩技术

如何将红外探测器采集的高动态范围的数据压缩为低动态范围图像数据的同时,能尽可能地保留图像的信息,提高图像的对比度一直是一个技术难点。针对这一问题,本文提出了一种新的红外图像压缩方法。该方法引入了直方图信息,通过对直方图进行分割,区分背景区域像素和目标区域像素; 然后计算压缩映射模型; 最后结合分割后的直方图对图像的像素采用不同强度的对比度增强。本文算法利用直方图区分背景区域像素与目标区域像素,在增强图像对比度时,能有效抑制背景噪声。通过实验对比,结果表明,本文所提出的算法更能较好地突出图像的细节,增强图像对比度。     

尺度自适应暗通道先验去雾方法

在雾、霾等天气条件下,大气粒子的散射作用使环境的能见度偏低,视觉系统采集到的图像严重降质。基于暗通道先验的图像复原方法因其去雾效果自然、约束条件少,且易于实现等优点而受到广泛关注。但是,该方法的去雾效果受尺度（暗通道的求解半径）影响很大,对于不同场景的图像,不存在一个普遍适用的最优尺度。针对该问题,文中提出一种尺度自适应方法,根据图像的颜色和边缘特征自适应地调节暗通道的尺度范围,得到像素级的暗通道求解尺度,兼顾大尺度求解色彩失真小和小尺度求解光晕失真小等优点。此外,针对暗通道去雾方法会使天空光估计点落到前景区域的问题,提出了一种改进的天空光估计方法,可使估计点鲁棒地落到与其物理意义相符的背景区域。对多种雾化场景图像的处理结果表明:文中方法适应性强、去雾效果自然,且对比度提升显著。     

基于颜色衰减先验和视觉显著性的水下图像增强算法

针对水下拍摄的图片存在颜色失真、细节和边缘模 糊等特点,提出了一种基于颜色衰减先验的水下图像增强算法。首先在计算暗通道函数时,用最小值滤波去噪。然后,对图片进行显著图处理,利用颜色先验法则完成深度估计。此滤波方法不仅能降噪,还可以防止颜色失真。最后,基于模型简化获得复原的图片,将其进行伽马变换进行校正,实现柔性去雾。实验结果表明,本文算法与几种典型的水下图像去雾算法相比,能够较好提高图像的清晰度和对比度,同时获得较好的图像颜色。     

Time-domain imaging of radar targets using sinogram restoration forlimited-view reconstruction

The time-domain image reconstruction problem can be formulated as a sinogram recovery problem. The sinogram recovery problem is to find a complete sinogram based on the measured incomplete sinogram. In this paper, we solve the sinogram recovery problem by using linear prediction techniques. Since the scattered field of a target can be written as a superposition of distinct specular reflections arising from scattering centers on the target, the trace of the scattering centers can be predicted using linear prediction with the change of the observation angle. Thus, the missing data may be predicted before reconstructing the image. Some useful results obtained using the proposed method are presented