Liquid crystal thermography and true-colour digital image processing

In the last decade thermochromic liquid crystals (TLC) and true-colour digital image processing have been successfully used in non-intrusive technical, industrial and biomedical studies and applications. Thin coatings of TLCs at surfaces are utilized to obtain detailed temperature distributions and heat transfer rates for steady or transient processes. Liquid crystals also can be used to make visible the temperature and velocity fields in liquids by the simple expedient of directly mixing the liquid crystal material into the liquid (water, glycerol, glycol, and silicone oils) in very small quantities to use as thermal and hydrodynamic tracers. In biomedical situations e.g., skin diseases, breast cancer, blood circulation and other medical application, TLC and image processing are successfully used as an additional non-invasive diagnostic method especially useful for screening large groups of potential patients. The history of this technique is reviewed, principal methods and tools are described and some examples are also presented.     

Edge linking and image segmentation by combining optical and digital methods

We present a hybrid method for segmentation of intensity images, which combines an optical contouring technique and digital algorithms for linking edge points or image segmentation. In a first stage, the digital image to be processed is displayed in a twisted-nematic liquid-crystal display (LCD), which is placed between a polarizer–analyzer pair at 45 deg (instead of 90 deg as occurs in standard LCDs). It is not difficult to demonstrate that the proposed setup produces a resultant image with very pronounced dark contours at middle intensity. After the optical preprocessing, two different digital algorithms are applied: an edge linking algorithm (modified chain code) and a simple thresholding technique for image segmentation. The proposed procedure works well with monochromatic and color images. The method could be useful as a robust technique for segmentation of large images in real-time, which presents potential applications in medical and biological imaging.     

基于特征点的对数极坐标变换图像配准算法

介绍了一种新的图像配准算法,可以很好地解决图像配准中的平移、旋转和缩放问题。算法的实现是首先使用SUSAN算子提取两幅图像的特征角点,剔除虚假的特征点(噪声点),然后使用改进对数极坐标变换和投影相关匹配算法实现特征点匹配;结合亚像素定位技术,可以进一步提高算法的精度。     

基于边缘与SURF算子的SAR与可见光图像配准方法

鉴于SAR(synthetic aperture radar)与可见光图像的成像机理存在很大差别,使得其同名特征的提取和配准十分困难,但在某些情况下,这两类图像的边缘存在一定的相关性。提出一种基于边缘与SURF(speed-up robust feature)算子的图像配准方法。通过适当预处理增强图像间的共性,采用综合性能比较好的Canny算子提取两幅图像共有的边缘特征,在边缘图像的基础上提取SURF特征;通过比值提纯法进行特征点粗匹配,RANSAC(random sample consensus)算法剔除误匹配点,计算仿射变换模型从而实现SAR与可见光图像的自动配准。实验结果表明:该算法的正确匹配率为100%,均方根误差为0.852个像素,配准精度达到亚像素水平。     

Digital image correlation based on a fast convolution strategy

In recent years, the efficiency of digital image correlation (DIC) methods has attracted increasing attention because of its increasing importance for many engineering applications. Based on the classical affine optical flow (AOF) algorithm and the well-established inverse compositional Gauss–Newton algorithm, which is essentially a natural extension of the AOF algorithm under a nonlinear iterative framework, this paper develops a set of fast convolution-based DIC algorithms for high-efficiency subpixel image registration. Using a well-developed fast convolution technique, the set of algorithms establishes a series of global data tables (GDTs) over the digital images, which allows the reduction of the computational complexity of DIC significantly. Using the pre-calculated GDTs, the subpixel registration calculations can be implemented efficiently in a look-up-table fashion. Both numerical simulation and experimental verification indicate that the set of algorithms significantly enhances the computational efficiency of DIC, especially in the case of a dense data sampling for the digital images. Because the GDTs need to be computed only once, the algorithms are also suitable for efficiently coping with image sequences that record the time-varying dynamics of specimen deformations.     

The application of improved block-matching method and block search method for the image motion estimation

Image block matching is one of the motion estimation methods for video inter-frame coding and digital image stabilization. The methods used for matching and searching will greatly affect the accuracy and speed of block matching. The block matching method based on the oblique vectors is suggested in this paper where matching parameters contain both horizontal and vertical vectors in the image blocks at the same time. Improved matching information can be obtained after making correlative calculations in the oblique direction. A novel search method of matching block based on the idea of simulated annealing is presented in this paper to improve the searching speed, accuracy and robustness in the fast operation of the block-matching motion estimation. The simulated annealing algorithm can easily escape from the trap of local minima effectively. With the two methods the block matching can be used for motion estimation at the real-time image processing system and high estimation accuracy can be achieved. An image stabilization system based on DSP (Digital Signal Processing) system is developed to verify this algorithm. Results show that both the matching accuracy and the search speed are improved with the methods presented.     

Parameter choice for optimized digital image correlation

Digital image correlation is a photomechanical technique utilized to measure displacement fields. Although the method has been used successfully in a variety of applications, there is a need for guidelines to choose correlation parameters and for an understanding of their link with the analyzed texture and their effect on the uncertainty of measured quantities. In this paper, two criteria are proposed from a texture study to evaluate the best compromise between measurement uncertainty and spatial resolution prior to any mechanical test. These criteria are then validated on a priori uncertainty evaluations with different textures, and on a real experiment when comparing image correlation results with strain gauge data.     

Incoherent digital holographic spectral imaging with high accuracy of image pixel registration

Fresnel incoherent correlation holography(FINCH) is a unique three-dimensional(3 D) imaging technique which has the advantages of scanning-free,high resolution,and easy matching with existing mature optical systems.In this article,an incoherent digital holographic spectral imaging method with high accuracy of spectral reconstruction based on liquid crystal tunable filter(LCTF) and FINCH is proposed.Using the programmable characteristics of spatial light modulator(SLM),a series of phase masks,none of whose focal lengths changes with wavelength,is designed and made.For each wavelength of LCTF output,SLM calls three phase masks with different phase constants at the corresponding wavelength,and CCD records three holograms.The spectral images obtained by this method have a constant magnification,which can achieve pixel-level image registration,restrain image registration errors,and improve spectral reconstruction accuracy.The results show that this method can not only obtain the 3 D spatial information and spectral information of the object simultaneously,but also have high accuracy of spectral reconstruction and excellent color reproducibility.     

Optical time-domain analog pattern correlator for high-speed real-time image recognition

The speed of image processing is limited by image acquisition circuitry. While optical pattern recognition techniques can reduce the computational burden on digital image processing, their image correlation rates are typically low due to the use of spatial optical elements. Here we report a method that overcomes this limitation and enables fast real-time analog image recognition at a record correlation rate of 36.7 MHz--1000 times higher rates than conventional methods. This technique seamlessly performs image acquisition, correlation, and signal integration all optically in the time domain before analog-to-digital conversion by virtue of optical space-to-time mapping.     

Digital color holographic recording and reconstruction using synthetic aperture and multiple reference waves

This paper presents a method for recording and reconstructing high-quality digital color holographic images. The synthetic aperture technique is used to improve the resolution of the reconstructed image and also reduce the speckle size in the reconstruction plane. Subsequently, the multiple reference wave technique is used to suppress speckle noise in the reconstructed color holographic image by superposing speckle fields with different distributions. The final high-quality color holographic image is obtained due to the resolution improvement and speckle noise reduction achieved by the two techniques. Our method has potential applications in the digital color holographic displays.     

舰船小目标图像配准算法

当舰船目标距离红外/可见光复合导引头较远的时候,红外与可见光图像中的目标信息微弱,可供提取的特征较少且差异较大,传统的图像配准算法很难适用.针对该问题,本文提出一种基于传感器参量的图像配准算法,首先根据红外与可见光传感器的成像模型将图像配准分解简化为视场配准与平移配准两个相对分离的步骤;然后利用传感器参量进行图像的视场配准;最后基于海天线和水平高通能量分布确定匹配点完成平移配准.仿真实验结果表明,该算法具有较高的配准准确度,可以应用于实际远距离海上舰船的红外和可见光图像配准.     

Motion detection in moving background using a novel algorithm based on image features guiding self-adaptive Sequential Similarity Detection Algorithm

A novel efficient algorithm for motion detection in dynamic background was proposed. In image registration step, a feature-based and self-adaptive Sequential Similarity Detection Algorithm (SSDA) algorithm was proposed, which searches for matching position under constraints induced by image features with variational threshold. Then perform change detection by calculating and classifying the Mean Absolute Difference (MAD) around detected features in the middle frames of three consecutive images. Moving objects position was determined according to the rule that the feature from moving regions shows a lager MAD. Experiments on data sets of four typical scenes show that the improved registration algorithm is accurate and costs less than 0.4 s in computation, much faster compared with other four methods, and the proposed Dual Maximum Mean Absolute Difference Algorithm (DMMADA) can obtain a robust set of moving object features. Our algorithm can be used for fast detection of moving targets in dynamic background as well as change detection.     

Accelerating image registration of MRI by GPU-based parallel computation

Automatic image registration for MRI applications generally requires many iteration loops and is, therefore, a time-consuming task. This drawback prolongs data analysis and delays the workflow of clinical routines. Recent advances in the massively parallel computation of graphic processing units (GPUs) may be a solution to this problem. This study proposes a method to accelerate registration calculations, especially for the popular statistical parametric mapping (SPM) system. This study reimplemented the image registration of SPM system to achieve an approximately 14-fold increase in speed in registering single-modality intrasubject data sets. The proposed program is fully compatible with SPM, allowing the user to simply replace the original image registration library of SPM to gain the benefit of the computation power provided by commodity graphic processors. In conclusion, the GPU computation method is a practical way to accelerate automatic image registration. This technology promises a broader scope of application in the field of image registration.     

A novel chaos-based bit-level permutation scheme for digital image encryption

Confidentiality is an important issue when digital images are transmitted over public networks, and encryption is the most useful technique employed for this purpose. Image encryption is somehow different from text encryption due to some inherent features of image such as bulk data capacity and high correlation among pixels, which are generally difficult to handle by conventional algorithms. Recently, chaos-based encryption has suggested a new and efficient way to deal with the intractable problems of fast and highly secure image encryption. This paper proposes a novel chaos-based bit-level permutation scheme for secure and efficient image cipher. To overcome the drawbacks of conventional permutation-only type image cipher, the proposed scheme introduced a significant diffusion effect in permutation procedure through a two-stage bit-level shuffling algorithm. The two-stage permutation operations are realized by chaotic sequence sorting algorithm and Arnold Cat map, respectively. Results of various types of analysis are interesting and indicate that the security level of the new scheme is competitive with that of permutation-diffusion type image cipher, while the computational complexity is much lower. Therefore the new scheme is a good candidate for real-time secure image communication applications.     

Determination of displacement distributions in bolted steel tension elements using digital image techniques

Digital imaging methods have found a great interest in various engineering fields to study stress-deformation characteristics of materials. Recent enhancements in visual instrumentation with the availability of cost-effective hardware and software products make the digital imaging techniques a viable tool to replace direct strain or displacement measurement methods in engineering applications. In this study, deformation characteristics of bolted steel connections are investigated by calculating in-plane displacement distributions using digital image correlation method (DIC). Validation of the method is presented by comparing the strains measured in standard tension specimens using electrical resistance strain gages and the DIC method. Finite element analysis of the connection specimen is also performed to compare the in-plane displacement distributions calculated from both methods. Results from the validation process indicate that the strains obtained from the DIC method compare well with the results of strain gages. The findings also indicate that the displacement distributions calculated from the finite element method may differ from those of the DIC method in terms of distribution pattern, and the location and magnitude of the extreme values of displacements. It is suggested that the proposed method can be used to determine the in-plane displacement distributions for the bolted connections, hence to evaluate their deformation characteristics under loading.     

Study of mutual information multimodality medical image registration based on modified simplex optimization method

Because of a different imaging mechanism and highly complexity of body tissues and structures. Different modality medical images provide non-overlay complementary information. This has very important significance for multimodal medical image registration. Image registration is the first and key part of problem to be solved in the integrations. When the spatial position of two medical images is same, the registration could be achieved. For two CT and PET images, the principal axis method is adopted to achieve the rough registration. The modified simplex algorithm is employed to implement global search using the mutual information as similarity measure. The initial registration parameters are achieved through principal axis Based on the results of test, improved simplex method can adjust reflecting distance. Stepped-up optimization algorithm on the new experimental points through the methods of “reflection”, “enlargement”, “shrinkage” or “global systolic”. A mutual information registration based on modified simplex optimization method is presented in this paper to improve the speed of medical image registration.Results indicate that the proposed registration method prevents the optimizing process from falling into local extremum and improves the convergence speed while keeping the precision. The accurate registration of multimodal image with different resolutions is achieved.     

针对特定场合的图像恢复算法实验研究

介绍了数字图像恢复技术的原理和主要的恢复算法,针对离焦退化、运动退化和高斯退化等不同应用场合,结合各种评价函数分析比较了维纳滤波、约束最小二乘法、Lucy-Richardson和最大熵法在图像恢复中的各自特点。对实际拍摄的离焦模糊图片进行了恢复处理,比较和印证了各算法的特性。总结了各算法在图像恢复中的特点以及各种图像质量评价函数的适用范围。     

多探测器拼接成像系统实时图像配准

依据已设计完成的基于同心球透镜的四镜头多探测器阵列拼接成像系统,对该系统图像拼接配准过程所采用的特征检测提取、特征向量匹配与筛选、空间变换模型参数估计等算法进行了研究。首先,采用Fast-Hessian检测子提取参考图像和待配准图像的特征点,并生成加速鲁棒特征(SURF)描述向量。接着,采用快速近似最近邻(FANN)逼近搜索算法获得初始的匹配点对,并对匹配点对特征向量的欧式距离进行排序。然后,参照成像系统光学设计参数设定合理的阈值,筛选并保留下较好的匹配点对。最后,提出了一种改进的渐进式抽样一致性(IPROSAC)算法对空间变换矩阵模型进行参数估计,从而得到参考图像与待配准图像的空间几何变换关系。实验结果表明:该算法对图像尺寸、旋转和光照变化都具有一定的不变性,特征匹配时间为0.542 s,配准变换时间0.031 s,配准误差精度小于0.1 pixel,可以满足成像系统关于图像配准实时性和准确性的要求,具有一定的工程应用价值。     

Improved algorithm for image encryption based on stochastic geometric moiré and its application

A technique based on optical operations on moiré patterns for image encryption and decryption is developed. In this method, an image is encrypted by a stochastic geometric moiré pattern deformed according to the image reflectance map. The decryption is performed using pixel correlation algorithm in the encrypted image and the stochastic geometrical moiré pattern. The proposed technique has a number of advantages over existing encryption techniques based on moiré gratings. No original moiré grating can be reconstructed only from the encrypted image. Stochastic moiré grating can be deformed in any direction what is an important factor of encryption security. Finally, the quality of the decrypted image is much better compared to decryption methods based on the superposition of the regular and deformed moiré gratings. The proposed technique has a great potential, because the process is performed using computational algorithms based on optical operations and optical components are avoided.