一种多滤波器组合导航数据融合方法

针对组合导航系统中使用单天线GPS接收机时导致姿态角不易收敛的问题,提出了一种互补滤波器和卡尔曼滤波器相结合的数据融合算法。该方法首先通过MEMS惯性传感器与磁强计设计了一种互补滤波算法。针对载体在变速运动过程中加速度计的倾角测量值有较大误差,影响互补滤波器输出精度的问题,通过GPS接收机和加速度计设计了卡尔曼滤波模型,将卡尔曼滤波器输出速度的微分量反馈给互补滤波器,实现了对互补滤波器中载体运动加速度的补偿。基于以上解算方法,以FPGA为核心处理器设计了组合导航系统并进行了车载实验。实验中,该方法有效补偿了汽车变速过程中的倾角测量误差,证明了该方法的有效性。     

基于灰度相关的图像匹配算法的改进

针对目前图像匹配算法中存在的匹配精度不高和匹配速度慢的缺点，对基于灰度相关的2类匹配算法——最小误差法和相关系数法进行了改进。最小误差法采用新的ML距离法，提出动态调整阈值的方法，既保证了匹配精度，又避免了局部噪声的影响；相关系数法对相关系数的计算公式进行了简化，并采用三步搜索策略进行匹配，以达到减少计算量和搜索位置的目的。实验证明：改进后的算法，在保证一定匹配精度的条件下，匹配速度大大提高，能够满足实际应用中的实时性要求。     

Multi-option image completion based on semantic matching image

In this paper, we propose a new image completion method based on high-accuracy semantic matching. Existing image completion approaches mainly focus on simple filling, ignoring creativity and accuracy in semantic matching. Our method can complete missing regions with more creative and semantically matching images as well as create a more seamless and consistent completed image.     

Improved keypoint descriptors based on Delaunay triangulation for image matching

In the current keypoint-based image matching methods, not all the keypoints can be reliably matched because of the influence of noise, illumination, and image distortion. In the paper, we propose a novel method based on the Delaunay triangulation to detect and remove possible mismatches. Given previously matched keypoints by a detector in two images, the proposed method utilizes four steps to remove the mismatched point pairs: first, triangulating keypoints in the reference image, and producing a graph consisting of edges that connects the keypoints; second, drawing a graph in the test image by connecting the corresponding points as same as in the reference image; third, detecting abnormal edges in the test image using special constraints; fourth, detecting and removing mismatched point pairs based on the abnormal edges. The experimental results show that the method can detect the mismatches accurately and improve the robustness of current matching algorithms.     

Hybrid bio-inspired lateral inhibition and Imperialist Competitive Algorithm for complicated image matching

Bio-inspired intelligent algorithms, such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), have been applied to solve image matching problems. However, due to high computational complexity and premature convergence problems associated with these methods, they have limitations in defining the global optimal matcher efficiently and accurately. To address these problems, we proposed a hybrid bio-inspired optimization approach, coupling the lateral inhibition mechanism and Imperialist Competitive Algorithm (ICA), to solve complicated image matching problems. With the adoption of the lateral inhibition mechanism, the global convergence of conventional ICA algorithms has been greatly improved. We demonstrate the efficiency and feasibility of the proposed approach by extensive comparative experiments.     

基于特征点匹配的电子稳像技术

为获得高质量视频输出序列,电子稳像技术常被用来去除成像设备所摄取的图像序列中的随机抖动。本文首先介绍了电子稳像的国内外发展现状。然后,从电子稳像技术中的运动估计模块出发,描述了国内外近年来出现的直接求取运动估计算法以及各种基于特征点匹配的运动估计方法,并对运动校正和运动补偿模块的算法进行了评述。最后综合分析了稳像算法的难点以及未来发展趋势,提出基于特征匹配的电子稳像技术的发展方向。     

A hybrid Particle Chemical Reaction Optimization for biological image matching based on lateral inhibition

In this paper, a hybrid Particle Chemical Reaction Optimization (PCRO) algorithm and lateral inhibition is proposed to solve the image matching problem. Lateral inhibition has the ability to enhance the characters of image, which can help to improve the accuracy of image matching. In order to overcome the shortcomings of basic Chemical Reaction Optimization (CRO) algorithm, we improve CRO by proposing PCRO which inspired from the thought of Particle Swarm Optimization (PSO). Comparative experimental results in image matching show that our proposed hybrid method performs much better than other bio-inspired algorithms.     

Cauchy Biogeography-Based Optimization based on lateral inhibition for image matching

In this paper, a hybrid method of Cauchy Biogeography-Based Optimization (CBBO) and Lateral Inhibition (LI) is proposed to complete the task of complicated image matching. Lateral inhibition mechanism is adopted for image pre-process to make the intensity gradient in the image contrastively strengthened. Biogeography-Based Optimization (BBO) is a bio-inspired algorithm for global optimization which is based on the science of biogeography, searching for the global optimum mainly through two steps: migration and mutation. To promote the optimization performance, an improved version of the BBO method using Cauchy mutation operator is proposed. Cauchy mutation operator enhances the exploration ability of the algorithm and improves the diversity of population. The proposed LI-CBBO method for image matching inherits both the advantages of CBBO and lateral inhibition mechanism. Series of comparative experiments using Particle Swarm Optimization (PSO), LI-PSO, BBO and LI-BBO have been conducted to demonstrate the feasibility and effectiveness of the proposed LI-CBBO.     

一种结合ORB特征匹配的均值漂移目标跟踪算法

针对传统的mean-shift跟踪算法基于单一颜色特征空间,在复杂背景下难以对目标进行准确跟踪这问题,提出了一种结合ORB特征匹配的mean-shift目标跟踪算法。该算法在mean-shift算法的基础上利用改进的ORB特征匹配算法修正目标跟踪窗口并实时更新目标特征模板,通过计算前后两帧图像中目标中心的欧式距离与色彩模板的巴氏距离来判定跟踪是否失败,当目标跟踪失败时,不改变目标模板,继续搜索下一帧图像中的目标。实验结果表明,与均值漂移算法和基于其他同类特征的改进算法相比,该算法提高了在复杂背景下目标跟踪的精度,并能满足实时性要求。     

基于图像分离块操作的快速模板匹配跟踪算法

传统的模板匹配跟踪算法存在运算量大和实时性差的缺陷,限制了它的应用范围。针对这一问题,在已有的基于位置预测相关跟踪算法的基础上,提出了利用图像分离块操作对相关跟踪算法进行改进,进一步减少相关跟踪算法的计算量,以满足系统的实时性要求。对改进算法进行了模拟仿真实验验证。仿真结果表明：该改进算法不仅在很大程度上减少了计算量,提高了跟踪系统的实时性,而且能够有效地减少随机噪声的影响,使得跟踪更加快速准确。     

用于像移探测的位平面匹配改进算法

像移探测作为电子稳像的重要的步骤,直接影响稳像的精度和速度。针对传统位平面匹配算法的局限,对各阶位平面的探测效果进行了综合测试,并提出了一种改进方案,即对位平面4,5经过下采样后组成一个合成位平面来进行匹配。研究了匹配块大小变化对位平面算法的影响,比较了相邻帧和固定帧两种参考帧选取方法的优劣。实验表明,改进的位平面匹配算法提高了位平面算法的稳健性,在没有增加计算量的前提下,算法精度达到了与全搜索块匹配法相当的程度。     

基于IECM特征匹配的红外弱点目标快速检测算法

提出了一种新的复杂背景下低信噪比红外弱点目标检测算法。根据红外弱点目标在图像中的三维空间特征,从空间认知的角度出发,将三维的灰度分布特征转化为二维的等高线曲线特征,建立红外图像的等高线图(IECM)描述,利用图论中的树结构(等高线树)形式化地表达等高线的空间关系,在此基础上,给出弱点目标检测的等高线树检测准则,同时给出了等高线划分等级的选择方法。理论分析与实验结果表明,该算法具有良好的检测性能,且结构简单,利于硬件实时实现。在信噪比为1.4的情况下,对红外图像序列的检测概率为96.3%。     

一种双波段图像实时融合实验系统

针对在紫外检测中可见光与紫外图像融合的实际需要,研究了实时融合技术。建立了一种以高性能数字信号处理器TMS320DM642为核心的双波段图像实时融合实验系统。介绍了系统的设计原理、各组成部分的功能及其特点。结果表明,该实验系统原理可行,能对可见光和紫外图像进行高速采集和实时隔合。     

A new image encryption algorithm based on hyper-chaos

This Letter presents a new image encryption scheme, which employs an image total shuffling matrix to shuffle the positions of image pixels and then uses a hyper-chaotic system to confuse the relationship between the plain-image and the cipher-image. The experimental results demonstrate that the suggested encryption algorithm of image has the advantages of large key space and high security, and moreover, the distribution of grey values of the encrypted y image has a random-like behavior.     

A novel blind digital watermarking algorithm for embedding color image into color image

A robust and blind watermarking technique for dual color images is proposed in this paper. According to the energy concentrating feature of DCT, the two-level DCT is introduced and used to embed color watermark image into color host image, which is completely different with the traditional DCT. For reducing the redundancy of watermark information, the original color watermark image is compressed by the proposed compression method. After two-level DCT, nine AC coefficients in different positions of each sub-block are selected and quantified to embed watermark information. Moreover, only the extraction rules are used to extract watermark from the watermarked image without resorting to the original host image or watermark image. Experimental results show that the proposed watermarking algorithm can effectively improve the quality of the watermarked image and the robustness of the embedded watermark against various attacks.     

基于SIFT匹配的全局运动估计方法

提出了一种基于SIFT(Scale invariant feature transform)匹配的全局运动估计算法.在SIFT初匹配的基础上,对每一个原始匹配特征点,利用所在尺度的邻域灰度信息,对其加权平均后再进行匹配,进而去除误配点.精炼后的匹配点集合作为求解全局运动参数模型的对应数据,采用最小二乘法计算模型参数.在...     

A piecewise local regularized Richardson-Lucy algorithm for remote sensing image deconvolution

As it is not possible to obtain an accurate point spread function (PSF) in remote sensing imaging, classic deconvolution methods such as Wiener filtering often introduce strong noise and ringing artifacts, which contaminate the restored images. In this paper, we modify the standard Richarson-Lucy (RL) algorithm with a piecewise local regularization term and combine it with residual deconvolution method. Experimental results show that it is effective in suppressing negative effects, and images with rich details and sharp edges are obtained.     

Calibration for stereo vision system based on phase matching and bundle adjustment algorithm

Calibration for stereo vision system plays an important role in the field of machine vision applications. The existing accurate calibration methods are usually carried out by capturing a high-accuracy calibration target with the same size as the measurement view. In in-situ 3D measurement and in large field of view measurement, the extrinsic parameters of the system usually need to be calibrated in real-time. Furthermore, the large high-accuracy calibration target in the field is a big challenge for manufacturing. Therefore, an accurate and rapid calibration method in the in-situ measurement is needed. In this paper, a novel calibration method for stereo vision system is proposed based on phase-based matching method and the bundle adjustment algorithm. As the camera is usually mechanically locked once adjusted appropriately after calibrated in lab, the intrinsic parameters are usually stable. We emphasize on the extrinsic parameters calibration in the measurement field. Firstly, the matching method based on heterodyne multi-frequency phase-shifting technique is applied to find thousands of pairs of corresponding points between images of two cameras. The large amount of pairs of corresponding points can help improve the accuracy of the calibration. Then the method of bundle adjustment in photogrammetry is used to optimize the extrinsic parameters and the 3D coordinates of the measured objects. Finally, the quantity traceability is carried out to transform the optimized extrinsic parameters from the 3D metric coordinate system into Euclid coordinate system to obtain the ultimate optimal extrinsic parameters. Experiment results show that the procedure of calibration takes less than 3 s. And, based on the stereo vision system calibrated by the proposed method, the measurement RMS (Root Mean Square) error can reach 0.025 mm when measuring the calibrated gauge with nominal length of 999.576 mm.     

A complex image reconstruction algorithm for real-time measurement of transient field

Optical CT is now expanding into reconstruction from few views or limited-view range projection considering the economy and practicality. To solve the conflict of velocity and precision, which are two main aims that image reconstruction algorithm pursued, an innovative complex image reconstruction algorithm for real-time measurement of transient field is proposed. This method reconstructs computerized tomography (CT) image firstly by frequency spectrum approach reconstruction technique (FSART) and then by modified simultaneous algebraic reconstruction technique (MSART) and can give a fast and precise reconstruction to complicated transient field.     

A novel algorithm of image fusion using shearlets

As a novel MGA (Multiscale Geometric Analysis) tool, shearlets are equipped with a rich mathematical structure similar to wavelets, which are associated to a multi-resolution analysis. Recently, shearlets have been used in image denoising, sparse image representation and edge detection. In this paper, as shearlet transform has the features of directionality, localization, anisotropy and multiscale, it is introduced into image fusion to obtain a fused image. The image could be decomposed by shearlet transform in any scale and any direction, and the detail information can be caught easily. Several different experiments are adopted to demonstrate that the fusion results based on shearlet transform contain more detail and smaller distortion information than any other methods does.