Digital image encryption with chaotic map lattices

This paper proposes a secure approach for encryption and decryption of digital images with chaotic map lattices. In the proposed encryption process,eight different types of operations are used to encrypt the pixels of an image and one of them will be used for particular pixels decided by the outcome of the chaotic map lattices. To make the cipher more robust against any attacks,the secret key is modified after encrypting each block of sixteen pixels of the image. The experimental results and security analysis show that the proposed image encryption scheme achieves high security and efficiency.     

A study on particle identification in PTV particle mask correlation method

An algorithm for particle identification in PTV, which is classified in the category?particle mask correlation method, is presented and tested. A typical brightness pattern of a particle image is referred to as a particle mask. The particle mask is centered on a pixel in the image plane and the cross correlation between the particle mask and a region of the image plane centered on the given pixel is calculated. The particle mask is scanned over the entire image plane and the cross correlation coefficient is calculated at each pixel location. Small subareas with high correlation coefficients indicate central areas of particle images.     

Single-shot subpixel response measurement with an aperture array pixel mask

We first point out that the subpixel response function is another kernel function in digital imaging. Then we show that the subpixel response function of CMOS imaging sensor pixels can be measured with an aperture array pixel mask in a single-shot image capture. Our technique permits high-resolution subpixel response function measurement of imaging pixels for superresolution imaging applications.     

An ensemble template algorithm for extracting targets from blurred infrared images

In this paper, an ensemble template algorithm is proposed to extract targets from blurred infrared images. First, the image pixels are divided according to their gray values into three pixel sets, a target set, a background set and the third set without class label. Second, the neighborhood statistical characteristics for each pixel are calculated as its template features. Third, ensemble detectors are designed using target pixels and background pixels based on their template features, and these ensemble detectors are used to detect the third pixel set. To evaluate the performance of the proposed extraction algorithm, this paper compares the ensemble template with other extraction algorithms using blurred infrared image of hand trace. Experimental results show that the ensemble template algorithm proposed in this paper exhibits better extraction performance.     

Target extraction from blurred trace infrared images with a superstring galaxy template algorithm

Accurate and efficient targets extraction from blurred trace infrared images has very important meaning for latent trace evidence collection in crime scene. Based on the superstring theory, a superstring galaxy template extraction algorithm for infrared trace target is presented. First, all of the pixels are divided into three classes: target pixels, background pixels and blurred pixels. Next, the superstring template characteristics for every pixel in a blurred infrared image are calculated as the features of each pixel. Finally, a galaxy covering algorithm is proposed, target pixels and background pixels are used for training the galaxy covering domain of every galaxy classifiers, and these classifiers will divide each blurred pixel into two classes: a target pixel or a background pixel. Experimental results indicate that the superstring galaxy template algorithm can improve the target extraction rate and reduce the extraction error rate.     

拉普拉斯约束低秩表示的高光谱图像异常检测

伴随高光谱图像的广泛使用,高光谱图像技术得到长足的发展,其中高光谱图像异常检测技术越发受到重视。为了解决传统高光谱图像异常检测技术的实用性和检测效果不佳的问题,提出一种新颖的低秩表示检测算法。对于高光谱图像,大部分背景像元均可以被少量主要的背景像元组合近似地表示,且它们的表示系数将会位于低秩的空间中。在剩下无法被主要背景像元表示的稀疏部分中存在着异常像元,则可以被检测算法提取出来。在低秩表示中,背景像元字典的构建将会影响高光谱图像中背景像元的表示。如直接从现有高光谱图像中提取背景像元构建字典,会导致异常像元对背景像元字典的污染。而利用待检测高光谱图像观测数据和由光谱组成原理可合成的潜在未观测数据来构建背景像元字典,提取出背景像元的主要特征,有利于更好地分离出稀疏异常像元的信息。并且高光谱图像数据存在高维几何结构特点,通过引入拉普拉斯矩阵来约束空间中局部相似的像元对于待检测像元的表示作用,获得更接近于真实的表示系数。实验结果分别在仿真数据和真实数据上验证,与传统方法相比,提出的方法通过有效地突出异常像元提高了检出率和抑制了背景像元,降低了误检率。     

Encrypting image by assembling the fractal-image addition method and the binary encoding method

The fractal-image addition method and the binary encoding method are assembled to form a hybrid method for encrypting a digital covert image. For this hybrid method, a host image is used to create an overt image with the information of the covert image. First, the fractal-image addition method is used to add some fractal images and the covert image to form an image-mixing matrix. Then, all the pixel values of the image-mixing matrix are transferred into binary data. Finally, the binary data are encoded into the host image to create an overt image. The pixels of the overt image contain eight groups of codes used for reconstructing the covert image. The eight groups of codes are identification codes, row amount codes, covert-image dimension codes, fractal-image amount codes, starting-pixel codes, character amount codes, character codes, and information codes. The overt image and the host image look almost the same for eyes. Furthermore, the covert image can be directly reconstructed from the overt image without using the host image. The most important feature is that the reconstructed covert image is identical to the original covert image, i.e. there is no distortion in the decoding work.     

Encryption and decryption of images with chaotic map lattices

We propose a secure algorithm for direct encryption and decryption of digital images with chaotic map lattices. The basic idea is to convert, pixel by pixel, the image color to chaotic logistic maps one-way coupled by initial conditions. After small numbers of iterations and cycles, the image becomes indistinguishable due to inherent properties of chaotic systems. Since the maps are coupled, the image can be completely recovered by the decryption algorithm if map parameters, number of iterations, number of cycles, and the image size are exactly known.     

基于深度优先遍历的图像边缘检测方法

图像边缘识别是图像处理的重要组成。提出一种基于深度优先遍历的梯度分割算法,这种算法首先构造像素点的数据结构,然后从图像任意点出发,估算该点附近的像素点并获取梯度值,如果该点满足边缘点的特征,则从该点出发深度遍历寻找垂直于梯度方向上的边缘点,并标记访问过的点。如果该方向上没有满足条件的点则回退,从某个具有仅次于最大梯度值的方向继续遍历,并标记开始遍历的点为角点,直至遍历全图。该算法将图像的边缘点和角点明显地分割出来,便于识别,对带有不同类型的噪声图像进行处理也可取得较满意效果。     

列图像中遮挡缺损图像补偿算法

针对动态图像的遮挡缺损问题,提出了基于图像块的帧间预测算法,可以检测出序列图像中的遮挡缺损区域;利用帧间灰度相关性修正补偿算法进行遮挡缺损区域补偿,利用修正的像元对缺损区域进行补偿能够克服传统插值补偿算法补偿痕迹明显的缺点.仿真结果表明:该算法补偿处理区域与邻域灰度过渡平滑,消除了补偿痕迹,补偿效果比较理想.     

Multifocus image fusion scheme using focused region detection and multiresolution

To solve the fusion problem of the multifocus images of the same scene, a novel algorithm based on focused region detection and multiresolution is proposed. In order to integrate the advantages of spatial domain-based fusion methods and transformed domain-based fusion methods, we use a technique of focused region detection and a new fusion method of multiscale transform (MST) to guide pixel combination. Firstly, the initial fused image is acquired with a novel multiresolution image fusion method. The pixels of the original images, which are similar to the corresponding initial fused image pixels, are considered to be located in the sharply focused regions. By this method, the initial focused regions can be determined, and the techniques of morphological opening and closing are employed for post-processing. Then the pixels within the focused regions in each source image are selected as the pixels of the fused image; meanwhile, the initial fused image pixels which are located at the focused border regions are retained as the pixels of the final fused image. The fused image is then obtained. The experimental results show that the proposed fusion approach is effective and performs better in fusing multi-focus images than some current methods.     

基于菲涅耳全息图和离散余弦变换的“盲数字水印”技术

基于光学菲涅耳全息图和相位密码板,结合离散余弦变换,设计了一种新的正实值编码的“盲数字水印”计算方法.相位密码板是多个点光源的菲涅耳衍射光场的相角之和,原始水印图像在其菲涅耳衍射域中与通过相位密码板的参考光作相干叠加,形成菲涅耳全息图;之后将其嵌入到原始宿主图像的离散余弦变换中,同时将此叠加水印信息的原像素值用其邻近的原像素均值来替换;通过作逆离散余弦变换,获得了已嵌入水印信息的正实数值的目标图像;通过对载有水印信息的目标图像作逆运算,从中提取了原始水印图像.数值计算结果表明：该水印计算法对JPEG有损压缩、剪切、噪音污染和重采样等攻击,具有很强的鲁棒性.由于本算法属“盲数字水印”技术,以及水印信息的灵活嵌入和多重密钥（衍射距离、多个点光源位置等）的随意选择,从而使该算法具有很高的安全性和实用价值.     

Multiplexing encryption technique by combining random amplitude and phase masks

We propose and demonstrate an encryption-selectable undercover multiplexing. We encrypt and multiplex images for storage by means of a random phase mask common to every image, covered with random amplitude masks different for each image. In order to get a correct decryption of the encoded information, we have to use the appropriate random amplitude mask; otherwise fake information is recovered. We employ a phase conjugation scheme to generate the recovering wavefronts. We analyze and compare the different alternatives and degrees of complexity this combination of masks brings to enhance the security of optical encrypting techniques. We also include an analysis on the advantages and disadvantages this undercover multiplexing protocol offers. We present digital simulations to demonstrate the soundness of the proposal.     

Speckle reduction by selective spatial-domain mask in digital holography

An improved method of using a selective spatial-domain mask to reduce speckle noise in digital holography is proposed.The sub-holograms are obtained from the original hologram filtered by the binary masks including a shifting aperture for being reconstructed. Normally, the speckle patterns of these sub-reconstructed images are different. The speckle intensity of the final reconstructed image is suppressed by averaging the favorable sub-reconstructed images which are selected based on the most optimal pixel intensity sub-range in the sub-holograms. Compared with the conventional spatial-domain mask method, the proposed method not only reduces the speckle noise more effectively with fewer sub-reconstructed images,but also reduces the redundant information used in the reconstruction process.     

基于光学菲涅耳衍射的"盲数字水印"技术

基于光学菲涅耳衍射,设计了一种新的“盲数字水印”计算方法。水印图像通过离散菲涅耳衍射变换成一复矩阵,将此复矩阵的实部和虚部分开,分别嵌入到宿主图像的不同位置中。通过将水印嵌入点的宿主图像的像素值更改为其近邻像素值的均值,而实现“盲水印”的提取。数值计算结果表明:该水印计算法对像素变换攻击具有很强的鲁棒性,如图像亮度、对比度和灰度曲线的调整;能抵抗JPEG有损压缩、剪切和噪声污染攻击;能抵抗对图像的重采样攻击,可从显示屏幕拷贝的图像中提取水印。由于该方法为使用者提供了灵活的水印嵌入方式和双重密钥的选取,以及提取水印不需要原始图像数据,因而使该方法具有很高的安全性和实用价值。     

Two-dimensional temporal coherence coding for super resolved imaging

In this paper, we present an approach that can be used for transmission of 2D spatial information through space-limited systems capable of transmitting even only a single spatial pixel. The input 2D object is illuminated with temporally incoherent illumination. The axial coherence length is very short and it equals only a few microns. Attached to the input object spatial random phase mask generates different axial shift for every pixel of the input. The temporal delays of the encoding (axial shifts) of every pixel are longer than the coherence length of the illuminating source. Therefore no temporal correlation exists between the various pixels of the input. A lens combines all spatial pixels into one point at its focal plane. Although the various spatial pixels were mixed together, since the random mask provided axial delay which was larger than the coherence length of the light source, the orthogonality between the spatial content of every pixel is preserved. The decoding system includes a lens that is positioned at the output of the resolution reduction system and it converts the output light into a plane wave containing all the spatial information of the original image mixed together in all of its pixels. By interfering this plane wave with the same plane wave after passing through the same random spatial coding mask, the spatial information of every pixel of the input object is recovered.     

Kalman filter based initial guess estimation for digital image correlation

In applications digital image correlation based algorithms often present a basis for analysis of movement/deformation of bodies. The sequence of the obtained images is analyzed for this purpose. Especially, in cases when the body׳s movement/deformation between two successive images is significant, the initial guess can have a major influence on the execution speed of the algorithm. In the worst case it can even cause the divergence of the algorithm. This was the inspiration to develop a new and unique approach for an accurate and reliable determination of an initial guess for each image pixel. Kalman filter has been used for this purpose. It uses past measurements of observed variable(s) for calculations. Beside that it also incorporates state space model of the actual system. This is one of the most important advantages provided by Kalman filter. The determined initial guess by the proposed method is actually close to the true one and it enables fast convergence. Even more important property of this approach is the fact that it is not path-dependant because each image pixel, which is defined in ROI, is tracked through the sequence of images based on its own past measurements and general state space model. Consequently, the proposed method can be used to analyze tasks where discontinuities between image pixels are present. The applied method can be used to predict an initial guess where reference and deformed subsets are related by translational and rotational motion. The advantages mentioned above are verified with numerical and real experiments. The experimental validations are performed by NR (Newton–Raphson) approach which is the most widely used. Beside NR method the presented algorithm is applicable for other registration methods as well. It is used as an addition for calculation of initial guesses in a sequence of deformed images.     

Balanced multi-image demons for non-rigid registration of magnetic resonance images

A new approach is introduced for non-rigid registration of a pair of magnetic resonance images (MRI). It is a generalization of the demons algorithm with low computational cost, based on local information augmentation (by integrating multiple images) and balanced implementation. Specifically, a single deformation that best registers more pairs of images is estimated. All these images are extracted by applying different operators to the two original ones, processing local neighbors of each pixel. The following five images were found to be appropriate for MRI registration: the raw image and those obtained by contrast-limited adaptive histogram equalization, local median, local entropy and phase symmetry. Thus, each local point in the images is supplemented by augmented information coming by processing its neighbor. Moreover, image pairs are processed in alternation for each iteration of the algorithm (in a balanced way), computing both a forward and a backward registration.The new method (called balanced multi-image demons) is tested on sagittal MRIs from 10 patients, both in simulated and experimental conditions, improving the performances over the classical demons approach with minimal increase of the computational cost (processing time around twice that of standard demons). Specifically, a simulated deformation was applied to the MRIs (either original or corrupted by additive Gaussian or speckle noises). In all tested cases, the new algorithm improved the estimation of the simulated deformation (squared estimation error decreased by about 65% in the average). Moreover, statistically significant improvements were obtained in experimental tests, in which different brain regions (i.e., brain, posterior fossa and cerebellum) were identified by the atlas approach and compared to those manually delineated (in the average, Dice coefficient increased of about 6%).The conclusion is that a balanced method applied to multiple information extracted from neighboring pixels is a low cost approach to improve registration of MRIs.     

顾及光谱混叠的高光谱相机任意方向侧扫几何成像

以移动平台的线推扫式高光谱相机横向推扫成像不同于以卫星平台或飞机平台的竖直摄影成像方式,其属于水平方向推扫竖直方向成像,存在投影面选择、空间方位确定以及光顾混叠等问题。针对上述情况,详细推导了适合于线阵高光谱相机地面推扫的影像像素地理参考模型,可以进行任意方向的地面横向推扫成像;结合影像的地面采样间隔大小及推扫成像的区域范围,给出了地理参考后影像格网划分的一般过程;同时,考虑到在影像格网划分过程中存在的舍入误差,以及在影像校正过程中采用传统直接光谱采样可能造成的光谱掺杂问题,提出了基于地理参考后相邻像素重叠面积作为权重系数进行加权融合的改进光谱采样方法。最后进行了大量地面横向推扫成像实验,并依据上述算法进行了影像畸变校正,验证了线阵影像几何畸变校正算法的有效性及鲁棒性,同时,对校正好后的影像选用多个样本点进行了光谱数据验证,实验表明改进后的光谱采样方法明显优于直接光谱采样算法,为同类产品的地面应用提供参考。     

同轴全息术用于粒子场测量的数值模拟

 采用数值方法模拟了同轴全息术测量粒子场的过程,对两种不同的数值算法＿直接傅里叶变换算法和卷积算法,进行了分析和比较,结果表明卷积算法符合实际要求。分析了记录图像的空间频谱及其对图像采样频率的要求,得出了在记录波长、采样间隔等条件一定的情况下的最小记录距离。对于一幅512×512像素的数字图像,若像元尺寸为6.7 μm,所用光波长为532 nm,则最小记录距离为43.2 mm。在此基础上对实验记录的振幅和相位型静态粒子的数字全息图,均得到了满意的数值再现像。