Area-adaptive simulated annealing for image reconstruction and restoration

Simulated annealing (SA) is a robust, stable, but computationally costly method for solving ill-posed image-restoration problems. We describe the use of a backprojection operator that identifies those regions of an object estimate that have the greatest likelihood of being in error at each step of the SA process. This reduces computational time by concentrating the computing effort of SA on those pixels most effective in reducing the reconstruction error. The performance of an area-adaptive SA algorithm is evaluated for the restoration of images blurred by a simple pillbox space-invariant and a biconical space-variant point-spread function typical of a depth-measuring optical system.     

The constrained two-dimensional guillotine cutting problem with defects: an ILP formulation,a Benders decomposition and a CP-based algorithm

This paper addresses a variant of two-dimensional cutting problems in which rectangular small pieces are obtained by cutting a rectangular object through guillotine cuts. The characteristics of this variant are (i) the object contains some defects, and the items cut must be defective-free; (ii) there is an upper bound on the number of times an item type may appear in the cutting pattern; (iii) the number of guillotine stages is not restricted. This problem commonly arises in industrial settings that deal with defective materials, e.g. either by intrinsic characteristics of the object as in the cutting of wooden boards with knotholes in the wood industry, or by the manufacturing process as in the production of flat glass in the glass industry. We propose a compact integer linear programming (ILP) model for this problem based on the discretisation of the defective object. As solution methods for the problem, we develop a Benders decomposition algorithm and a constraint-programming (CP) based algorithm. We evaluate these approaches through computational experiments, using benchmark instances from the literature. The results show that the methods are effective on different types of instances and can find optimal solutions even for instances with dimensions close to real-size.     

光学邻近效应与掩模特征尺寸的关系

依据物的空间频谱分布，部分相干成象理论及空间滤波概念，分析了投影光刻中的掩模特征尺寸与光学邻近效应的关系，并通过成象系统的数值孔长对ＯＰＥ的影响的模拟验证了分析结果。     

Depth extraction by using the correlation of the periodic function with an elemental image in integral imaging

We propose a depth extraction method by using the correlation between an elemental image and a periodic function in computational integral imaging. Because each elemental image corresponds to a different perspective of the three-dimensional (3-D) object, an elemental image is regarded as the sum of the periodic spatial frequencies depending on the depth of a 3-D object. In this regard, we analyze the property of correlation between the same periodic functions and vice versa. To show the feasibility of the proposed method, we carried out our experiment and presented the results.     

High-density optical recording using a solid immersion lens

A solid immersion lens attached to a conventional objective increases the effective numerical aperture (NA(eff)) of an optical pickup and yields an areal recording density proportional to (NA(eff))(2). One version of this device, with an effective (NA(eff)) of 1.7, should be capable of very high density storage but would probably need a sealed system. Another simple configuration enables the use of this method for optical data storage in an unsealed environment and extends the spatial cutoff frequency 1.5 times. Experiments with these devices are compared with the full vector field theory of this type of imaging system.     

Use of artificial neural networks on optical track width measurements

We have demonstrated recently that, by using an ultrastable optical interferometer together with artificial neural networks (ANNs), track widths down to 60 nm can be measured with a 0.3 NA objective lens. We investigate the effective conditions for training ANNs. Experimental results will be used to show the characteristics of the training samples and the data format of the ANN inputs required to produce suitably trained ANNs. Results obtained with networks measuring double tracks, and classifying different structures, will be presented to illustrate the capability of the technique. We include a discussion on expansion of the application areas of the system, allowing it to be used as a general purpose instrument.     

Multiframe superresolution of binary images

We describe a new algorithm for superresolving a binary object from multiple undersampled low-resolution (LR) images that are degraded by diffraction-limited optical blur, detector blur, and additive white Gaussian noise. Two-dimensional distributed data detection (2D4) is an iterative algorithm that employs a message-passing technique for estimating the object pixel likelihoods. We present a novel non-training-based complexity-reduction technique that makes the algorithm suitable even for channels with support size as large as 5 x 5 object pixels. We compare the performance and computational complexity of 2D4 with that of iterative backprojection (IBP). In an imaging system with an optical blur spot matched to the object pixel size, 2 x 2 undersampled measurement pixels, and four LR images, the reconstruction error measured in terms of the number of pixel mismatches for 2D4 is 300 times smaller than that for IBP at a signal-to-noise ratio of 38 dB.     

Three-dimensional object feature extraction and classification with computational holographic imaging

We address three-dimensional (3D) object classification with computational holographic imaging. A 3D object can be reconstructed at different planes by use of a single hologram. We apply principal component and Fisher linear discriminant analyses based on Gabor-wavelet feature vectors to classify 3D objects measured by digital interferometry. Experimental and simulation results are presented for regional filtering concentrated at specific positions and for overall grid filtering. The proposed technique substantially reduces the dimensionality of the 3D classification problem. To the best of our knowledge, this is the first report on the use of the proposed technique for 3D object classification.     

Effects of source shape on the numerical aperture factor with a geometrical-optics model

We study the effects of an extended light source on the calibration of an interference microscope, also referred to as an optical profiler. Theoretical and experimental numerical aperture (NA) factors for circular and linear light sources along with collimated laser illumination demonstrate that the shape of the light source or effective aperture cone is critical for a correct NA factor calculation. In practice, more-accurate results for the NA factor are obtained when a linear approximation to the filament light source shape is used in a geometric model. We show that previously measured and derived NA factors show some discrepancies because a circular rather than linear approximation to the filament source was used in the modeling.     

一种基于视图和支持向量机的三维物体识别方法

为提高三维物体识别系统性能并减少计算复杂性,本文提出了一种基于视图的方法.首先从三维物体的二维视图中提取颜色矩、纹理特征和仿射不变矩.颜色矩对于物体的大小和姿态不敏感且性能稳健.纹理特征可区别形状相似但外观不同的物体.仿射不变矩在物体发生仿射形变下具有不变性.本文将上述各种特征组合为23个分量的特征向量,送入支持向量机进行训练并识别.基于两种公开的三维物体数据库COIL-100和ALOI测试了本文方法性能.当每物体训练视角为36个(视角间隔10°)时,在两个数据库上的实验都达到了100%的识别率.进一步减少训练视角数量也达到较满意的识别性能,优于文献中的方法.     

Inverse scattering for frequency-scanned full-field optical coherence tomography

Full-field optical coherence tomography (OCT) is able to image an entire en face plane of scatterers simultaneously, but typically the focus is scanned through the volume to acquire three-dimensional structure. By solving the inverse scattering problem for full-field OCT, we show it is possible to computationally reconstruct a three-dimensional volume while the focus is fixed at one plane inside the sample. While a low-numerical-aperture (NA) OCT system can tolerate defocus because the depth of field is large, for high NA it is critical to correct for defocus. By deriving a solution to the inverse scattering problem for full-field OCT, we propose and simulate an algorithm that recovers object structure both inside and outside the depth of field, so that even for high NA the focus can be fixed at a particular plane within the sample without compromising resolution away from the focal plane.     

Motion tracking system in video based on extensive feature set

In recent years, object detection and tracking has been a dynamic research area. Rapid development of the multimedia and the associated technologies urge the processing of a huge database of video clips. The processing efficiency lies on the search methodologies utilised in the video processing system. Usage of unsuitable search methodologies may make the processing system ineffective. Hence, effective object detection and tracking system is an essential criterion for searching relevant videos from a huge collection of videos. This paper proposes a unique object detection and tracking system where video segmentation, feature extraction, object detection and tracking are combined perfectly using various features. Initially, the database video clips are segmented into different shots before performing the feature extraction process. The proposed system consists of two stages, namely, feature extraction and tracking of object in the video clips. In the feature extraction stage, firstly, colour feature is extracted based on colour quantisation. Next, edge density feature is extracted for the objects present in the query video. Then, the texture feature is extracted based on LGXP technique. Finally, based on these feature extracted, the object will be detected and the detected objects will be tracked by utilising both forward and backward tracking technique. The proposed methodology proved to be more effective and accurate in object detection and tracking.     

N-ocular volume holographic imaging

Volume holographic imaging utilizes Bragg selectivity to optically slice the object space of the imaging system and measure four- (three spatial and one spectral) dimensional object information. The N-ocular version of this method combines multiple-volume holographic sensors and digital postprocessing to yield high-resolution three-dimensional images for broadband objects located at long working distances. We discuss the physical properties of volume holography pertinent to imaging performance and describe two computational algorithms for image inversion based on filtered backprojection and least-squares optimization.     

流固耦合问题的网格更新与信息传递新方法

研究流固耦合问题中的网格技术。针对流体域的网格移动,提出基于映射结构化网格的插值更新的新方法,采用映射插值函数计算流体网格节点位移并与初始网格坐标值叠加,以获取流体新的节点坐标。对二维正方形、梭形及三维立方体流场网格更新开展数值计算。计算表明,该方法可保持原网格的拓扑关系,且更新速度快,更新质量好。使用约束反力分配法和投影插值法分别传递流体域到结构域、结构域到流体域的信息,运用基于该方法的自编程序对典型形体的结构流固耦合界面进行信息传递计算模拟。通过对比传递前后结构与流体的作用,验证了基于该方法的数值传递效果理想。     

Lensfree color imaging on a nanostructured chip using compressive decoding

We demonstrate subpixel level color imaging capability on a lensfree incoherent on-chip microscopy platform. By using a nanostructured substrate, the incoherent emission from the object plane is modulated to create a unique far-field diffraction pattern corresponding to each point at the object plane. These lensfree diffraction patterns are then sampled in the far-field using a color sensor-array, where the pixels have three different types of color filters at red, green, and blue (RGB) wavelengths. The recorded RGB diffraction patterns (for each point on the structured substrate) form a basis that can be used to rapidly reconstruct any arbitrary multicolor incoherent object distribution at subpixel resolution, using a compressive sampling algorithm. This lensfree computational imaging platform could be quite useful to create a compact fluorescent on-chip microscope that has color imaging capability.     

Unlockable Nanocomplexes with Self‐Accelerating Nucleic Acid Release for Effective Staged Gene Therapy of Cardiovascular Diseases

Nucleic acid (NA)‐based therapy is proposed to address serious diseases such as cardiovascular diseases (CVDs). Powerful NA delivery vehicles are essential for effective gene therapy. Herein, a novel type of delivery vehicle, an unlockable core–shell nanocomplex (Hep@PGEA) with self‐accelerating NA release, is structurally designed. Hep@PGEA is composed of disulfide‐bridged heparin nanoparticle (HepNP) core and low‐toxicity PGEA cationic shell. In comparison with NA, heparin, a negatively charged polysaccharide macromolecule, exhibits stronger interactions with cationic species. Upon the breakdown of redox‐responsive HepNP cores, unlocked heparin would interact with the outer cationic shells and replace the condensed NA to facilitate NA release. Such unique Hep@PGEA is successfully explored for effective miRNA–pDNA staged gene therapy of myocardial infarction (MI), one of the most serious CVDs. With the progression of MI, glutathione amounts in heart tissues increase. MiR‐499 (for the inhibition of cardiomyocyte apoptosis) and plasmid encoding vascular endothelial growth factor (for the promotion of angiogenesis) are sequentially delivered for systemic treatment of MI. Such treatment produces impressive results in restoring heart function and suppressing cardiac hypertrophy. Due to the wide existence of redox agents in cells, the proposed unlockable delivery nanovehicle and staged therapy strategy can provide new methods to effectively treat different serious diseases.     

Invariants under image perspective transformations: Theory and examples

The objective of this work is to develop automated techniques for recognizing the same objects in images that differ in scale, tilt, and rotation. Such perspective transformations of images are produced when aerial images of the same scene are taken from different vantage points. The algebraic methods developed previously do not utilize the intensity values of the images, i.e., their pixel gray levels. Since image features essential for object recognition, such as edges and local image textures, may be described in terms of derivatives and integrals of the image intensity, it is necessary to investigate whether certain differential and integral operators applied to different perspective views of the same object are also invariant under the perspective transformation. We proceed to derive new differential operators and their corresponding integral invariants for curves and planar objects. We introduce a variant form of Fourier expansion specially adapted to the projective transformation. Extensions to three dimensions are discussed, as well as applications to other image formation models such as synthetic aperture radar (SAR). These results are steps toward a computational model for perspective-independent object recognition.     

Implementation of multilens micro-optical systems with large numerical aperture by stacking of microlenses

In the field of micro-optics there is a demand for objectives with large numerical aperture (NA). One example is optical storage in which a NA greater than 0.5 is required. For planar microlenses the NA is determined by means of the maximal index difference and the degree of exchange and reaches typical values of 0.13-0.2. Thus stacking is needed to build high NA objectives from planar microlenses. An additional benefit of stacking lenses is the possibility to correct for different types of aberrations. We realized two stacked systems: an array of micro-objectives with a NA of 0.45 from three microlens arrays and a confocal sensor head from four microlens arrays and one pinhole array mask.     

Vector wave analysis for nonnormal incident rays in epimicroscopic refractive index profile measurements

We have investigated the effects of nonnormal incident rays in calculating the refractive index profile of a dielectric sample using the reflectance measurement data obtained with a scanning confocal epimicroscope and also by solving three-dimensional vector wave equations for linearly polarized light. The numerically calculated reflection data of tightly focused Gaussian beams with different numerical apertures (NAs) on planar surfaces with various refractive indices confirm that the reflectance increases with an increase in the NA of a focusing objective lens. This is due to the nonnormal incident ray components of a Gaussian beam. We have found that the refractive index obtained with the assumption of a normal incident beam is far from the real value when the NA of a focusing lens becomes larger than 0.5, and thus the variation in the reflectance for different angular components in a Gaussian beam must be taken into consideration while using a larger NA lens. Errors in practical refractive index calculation for an optical fiber based on a normal incident beam in reflectance measurements can be as large as 1% in comparison to real values calculated by our three-dimensional vector wave equations.     

A moment invariant for evaluating the chirality of three-dimensional objects

Chirality is an important feature of three-dimensional objects and a key concept in chemistry, biology and many other disciplines. However, it has been difficult to quantify, largely owing to computational complications. Here we present a general chirality measure, called the chiral invariant (CI), which is applicable to any three-dimensional object containing a large amount of data. The CI distinguishes the hand of the object and quantifies the degree of its handedness. It is invariant to the translation, rotation and scale of the object, and tolerant to a modest amount of noise in the experimental data. The invariant is expressed in terms of moments and can be computed in almost no time. Because of its universality and computational efficiency, the CI is suitable for a wide range of pattern-recognition problems. We demonstrate its applicability to molecular atomic models and their electron density maps. We show that the occurrence of the conformations of the macromolecular polypeptide backbone is related to the value of the CI of the constituting peptide fragments. We also illustrate how the CI can be used to assess the quality of a crystallographic electron density map.