实测端元光谱和多光谱图像之间的模拟与细分

地物光谱特性是遥感应用的基础。本文以渭干河-库车河三角洲绿洲为研究区,首先选取裸土、植被两类地物作为研究对象,通过TM传感器的光谱响应函数,实现了将野外实测端元光谱拟合为多光谱离散光谱。其次在对TM图像的光谱波段进行细分的基础上,利用光谱知识库的数据支持来模拟获取具有更高光谱分辨率的细分光谱光学遥感图像,深入开展两种尺度相互转换的研究。结果表明:一、拟和的多光谱与TM像元光谱具有很好的相关性,在此基础上,采用线性算法建立端元光谱与遥感图像像元光谱的转换模型,实现了从实测端元光谱尺度向遥感多光谱像元尺度的定量光谱转换,为遥感定量分析奠定了一定基础。二、细分光谱模拟图像的方法能够较为可靠的模拟出真实高光谱分辨率图像的信息,模拟方法可信,达到了推广和验证的效果。     

基于宽光谱光学遥感图像的细分光谱光学遥感图像的模拟

本文分析了现有遥感图像模拟方法的特点,介绍了地物波谱知识库的建立情况与应用意义,论述了光学传感器的成像特点及地面实测数据与遥感反演数据之间的转换关系.本文在对TM图像的光谱波段进行细划分的基础上,提出利用波谱知识库的数据支持来模拟获取具有更高光谱分辨率的细分光谱光学遥感图像的方法.本方法依据光谱数据库等先验知识的支持,通过遥感成像时辐射传输的模拟运算,在宽光谱光学遥感数据提供的图像纹理信息和地类信息的基础上,获取细分光谱波段的模拟光学遥感图像,同时避免了难以接受的计算量.细分光谱模拟图像的实验结果表明,本方法能够较为可靠的模拟出真实高光谱分辨率图像的信息,模拟方法可信.     

一种改进的遥感图像融合方法

针对传统的IHS变换和Mallat算法在融合多光谱图像和高空间分辨力图像时存在的不足,提出了一种将IHS变换和平稳小波变换相结合的遥感图像融合方法;另外,对多光谱图像和高空间分辨力图像因空间分辨力的不同而带来的融合图像中所存在的虚假轮廓问题,提出在融合过程中先定位虚假轮廓出现的位置,然后加以处理的方法.仿真结果表明,本文算法在光谱失真上小于IHS变换法,克服了Mallat算法存在的方块效应,同时较好的抑制了虚假轮廓.     

SAR图像与多光谱图像融合方法研究

本文针对SAR图像分辨率高、纹理信息多、斑噪影响大，而多光谱图像光谱信息丰富、分辨率较小的特点，提出了一种SAK与多光谱图像的数据融合算法。该方法分三步进行：首先使用粗糙集理论选取图像特征，在此基础上，对特征提取后的图像进行配准，配准中采用了数理统计中近似正态分布的方法，配准精度在一个像素以内，最后采用相关性加权的方法对配准后的SAK图像与多光谱图像进行融合。融合实验以LandSat的TM图像与Radsat的SAK图像为例，实验结果表明该方法取得了较好的融合效果。     

基于光谱特征和纹理特征协同学习的高光谱图像数据分类

高光谱遥感图像中包含有大量的高维数据,传统的有监督学习算法在对这些数据进行分类时要求获取足够多的有标记样本用于分类器的训练.然而,对高光谱图像中大量的复杂地物像元所属类别进行准确标注通常需要耗费极大的人力.在本文中,我们提出了一种基于半监督学习的光谱和纹理特征协同学习(STF-CT)--法,利用协同学习机制将高光谱图像光谱特征和空间纹理特征这两种不同的特征结合起来,用于小训练样本集下的高光谱图像数据分类问题.STF-CT算法充分利用了高光谱图像的光谱和纹理特征这两个独立视图,构建起一种有效的半监督分类方法,用于提升分类器在小训练样本集情况下的分类精度.实验结果表明该算法在小训练样本集下的高光谱地物分类问题上具有很好的效果.     

基于遥感图像散乱数据点的三角曲面片插值构造

基于散乱数据点集构造三角插值曲面的方法，在CAD／CAM、科学计算可视化、图像处理等领域有着广泛的应用。本文介绍一种基于遥感图像散乱数据点的三角曲面片插值构造方法。该方法通过在遥感图像上选取局部极值点来构成平面散乱数据点集，并在此基础上进行三角剖分、优化和三角插值曲面构造。此方法在海洋遥感图像多尺度分解处理应用中取得了较为理想的结果。     

一种用于高光谱图像分类的空谱协同编码方法

针对现有基于协同表示的分类算法对于高光谱遥感图像的空间光谱信息利用不充分而造成较低分类精度的问题,该文提出一种空谱协同编码方法用于高光谱图像分类。算法首先利用空间光谱信息对图像进行加权滤波。随后,对于协同编码模型,将空间光谱信息转化为空间光谱权重以对模型进行正则约束。在Indian Pines和University of Pavia真实数据集上的实验结果表明提出的算法能分别获得98.82%和99.09%的总体精度。实验证明了所提出的算法对高光谱遥感图像进行分类的有效性。     

基于形式概念分析的多光谱遥感影像波段选择

针对遥感图像特征选择和提取的波段选择,利用形式概念分析中属性约简的思想设计了波段约简选择算法。该方法利用遥感影像的信息量作为指标,将多光谱影像作为形式背景,各波段作为形式属性,通过属性约简得到核心属性即最优波段,这样不仅避免了多光谱遥感数据波段之间的相关性对波段选择的影响,还提高了选取训练样本的效率。最后采用了美国地球观测卫星Landsat拍摄的TM遥感影像数据进行实验,与常用的波段选择方法相比,本文的方法更为简便和高效。     

遥感图像融合技术及其在土地资源动态监测中的应用

论述遥感图像融合常见的技术方法、融合过程和类型，并以两种遥感图像融合方式为例说明遥感图像融合技术在土地资源动态监测中的应用前景。     

基于IHS变换的多光谱遥感图像有损压缩算法

提出了一种有效的多光谱遥感图像有损压缩算法,该算法根据多光谱遥感图像的数据特点,将IHS变换和整数小波变换相结合进行数据压缩.采用IHS变换去除谱间相关性;采用整数小波变换去除空间相关性,依据各个子带的重要程度,用自适应阈值进行量化,并分别对量化后的数据和重要图表采用固定比特平面编码和游程编码.实验结果表明,算法在保证平均PSNR≥33dB时,获得了较高的压缩比,并且算法硬件实现简单,对内存的需求低.     

Digital Forensics for Recoloring via Convolutional Neural Network

As a common medium in our daily life, images are important for most people to gather information. There are also people who edit or even tamper images to deliberately deliver false information under different purposes. Thus, in digital forensics, it is necessary to understand the manipulating history of images. That requires to verify all possible manipulations applied to images. Among all the image editing manipulations, recoloring is widely used to adjust or repaint the colors in images. The color information is an important visual information that image can deliver. Thus, it is necessary to guarantee the correctness of color in digital forensics. On the other hand, many image retouching or editing applications or software are equipped with recoloring function. This enables ordinary people without expertise of image processing to apply recoloring for images. Hence, in order to secure the color information of images, in this paper, a recoloring detection method is proposed. The method is based on convolutional neural network which is quite popular in recent years. Unlike the traditional linear classifier, the proposed method can be employed for binary classification as well as multiple labels classification. The classification performance of different structure for the proposed architecture is also investigated in this paper.     

Edge‐adaptive color interpolation for complementary color filter array

Complementary color filter array (CCFA) is widely used in consumer‐level digital video cameras, since it not only has high sensitivity and good signal‐to‐noise ratio in low‐light condition but also is compatible with the interlaced scanning used in broadcast systems. However, the full‐color images obtained from CCFA suffer from the color artifacts such as false color and zipper effects. These artifacts can be removed with edge‐adaptive color interpolation (ECI) approaches which are generally used in primary color filter array (PCFA). Unfortunately, the unique array pattern of CCFA makes it difficult that CCFA adopts ECI approaches. Therefore, to apply ECI approaches suitable for CCFA to color interpolation is one of the major issues to reconstruct the full‐color images. In this paper, we propose a new ECI algorithm for CCFA. To estimate an edge direction precisely and enhance the quality of the reconstructed image, a function of spatial variances is used as a weight, and new color conversion matrices are presented for considering various edge directions. Experimental results indicate that the proposed algorithm outperforms the conventional method with respect to both objective and subjective criteria. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 92–102, 2006     

基于支持向量机分类策略的多晶硅电池片色差检测

针对复杂颜色和纹理特征条件下,多晶硅电池片上的色差检测问题,提出了一种基于支持向量机分类策略的多晶硅电池片色差检测方法。首先对预处理后电池片图像进行颜色模型转换和通道分离,利用Otsu方法对单通道图像进行阈值分割处理,并计算各阈值图像的区域对比度,然后根据区域对比度情况选择合适的阈值图像,利用阈值图像所提供的信息提取图像特征;最后使用支持向量机分类器来判别电池片是否存在色差缺陷。实验结果表明提出的色差检测算法可以实现多晶硅电池片色差高效检测,色差缺陷检测的准确度、误检率和检测时间分别达到96.88%, 5％和109ms。     

Investigation of Residual Stress in 2D Plane Weave Aramid Fibre Composite Plates Using Moiré Interferometry and Hole‐Drilling Technique

Residual stress (RS) is crucial to the fabrications of woven composite plates and difficult to measure experimentally because of the complex structures of these plates. This study aims to investigate the RS in 2D plane weave aramid fiber composite plates using hole‐drilling technique coupled with moiré interferometry. A two‐step drilling method is proposed to solve the problems caused by the ‘peel up’ phenomenon, which facilitates the analyses of the obtained moiré patterns. The holes are deliberately selected at the intersection points of the symmetry axes of warp and weft yarns to obtain symmetrically released displacement fields. Moreover, finite element method calibration is conducted to measure RS using a model created based on the real structure of the woven composite. Based on the error analysis in numerical simulations, the less sensitive points are proposed for the RS calculation. The results show that the RS components of each specimen are compressive along the aramid yarns and tensile perpendicular to them. In addition, investigating of the influence of drilling depths on RS shows that RS decreases along the hole‐depth direction. Findings of this study are helpful for the manufacture and quality evaluation of woven aramid fibre composites.     

Macro and micro-residual stress distribution in 6061 Al-15 vol.% SiCw under different heat treatment conditions

The residual stress, RS, profiles in a 6061Al-15 vol.% SiC_w composite and in its unreinforced alloy have been determined by synchrotron radiation diffraction, SRD. The high spatial resolution achieved by this technique has allowed resolving the spatial dependence of all three principal components of the RS field with the sample radius. The micro and macro stress have been successfully separated revealing the different distribution along the sample cross section as a consequence of their different nature. In this way clear experimental evidence of theoretical works could be given.     

Fire Detection Method Based on Improved Fruit Fly Optimization-Based SVM

Aiming at the defects of the traditional fire detection methods, which are caused by false positives and false negatives in large space buildings, a fire identification detection method based on video images is proposed. The algorithm first uses the hybrid Gaussian background modeling method and the RGB color model to perform fire prejudgment on the video image, which can eliminate most non-fire interferences. Secondly, the traditional regional growth algorithm is improved and the fire image segmentation effect is effectively improved. Then, based on the segmented image, the dynamic and static features of the fire flame are further analyzed and extracted in the area of the suspected fire flame. Finally, the dynamic features of the extracted fire flame images were fused and classified by improved fruit fly optimization support vector machine, and the recognition results were obtained. The video-based fire detection method proposed in this paper greatly improves the accuracy of fire detection and is suitable for fire detection and identification in large space scenarios.     

基于局部估计的多光源图像颜色恒常性计算

目的解决多光源场景图像的颜色矫正问题。方法首先采用网格划分和关键点取样2种方法对多光源图像划分区域,然后对划分后的区域采用单光源颜色恒常性算法估计光源,把每一个区域对场景光源颜色的贡献整合为复合光源颜色作为多光源场景的近似估计,最后采用对角模型进行矫正,并将此方法与单独用单光源颜色恒常性算法估计做对比。结果通过对多光源图像划分区域,可以弱化多个光源对图像的影响,与单独用单光源颜色恒常性算法估计对比,对图像的矫正效果显著。结论通过局部估计多光源图像,所提出的方法可以有效解决多光源室外场景图像的颜色恒常性问题。     

Inkjet printing of conjugated polymer precursors on paper substrates for colorimetric sensing and flexible electrothermochromic display

Inkjet-printable aqueous suspensions of conjugated polymer precursors are developed for fabrication of patterned color images on paper substrates. Printing of a diacetylene (DA)-surfactant composite ink on unmodified paper and photopaper, as well as on a banknote, enables generation of latent images that are transformed to blue-colored polydiacetylene (PDA) structures by UV irradiation. Both irreversible and reversible thermochromism with the PDA printed images are demonstrated and applied to flexible and disposable sensors and to displays.     

金属 /介质型纳米复合变色膜

变色膜是一种随观察角度不同而改变颜色的多层光学薄膜,在防伪领域有着重要的应用。本工作给出了金属／介质型鸾以膜的膜系设计,包括各膜层的最佳厚度或最小厚度要求;针对现行制备工艺存在的生产周期长、成本高问题,提出了一种制备金属／介质型变色膜的新工艺－纳米复合工艺（NCT）,并用NCT制备了变色膜样品,对样品的结构和光谱进行了测量。使用NCT,可望大幅度地降低变色膜的制备成本。