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Defocus is an important factor that causes image quality degradation of optoelectronic tracking equipment in the shooting range. In this paper, an improved blind/referenceless image spatial quality evaluator (BRISQUE) algorithm is formulated by using the image characteristic extraction technology to obtain a characteristic vector (CV). The CV consists of 36 characteristic values that can effectively reflect the defocusing condition of the corresponding image. The image is evaluated and scored subjectively by the human eyes. The subjective evaluation scores and CVs constitute a set of training data samples for the defocusing evaluation model. An image database that contains sufficiently many training samples is constructed. The training model is trained to obtain the support vector machine (SVM) model by using the regression function of the SVM. In the experiments, the BRISQUE algorithm is used to obtain the image feature vector. The method of establishing the image definition evaluation model via SVM is feasible and yields higher subjective and objective consistency. [ABSTRACT FROM AUTHOR]

Phase-measuring profilometry (PMP) is an important technique for image analysis in optical non-destructive testing (NDT). Its measurement accuracy is significantly affected by gamma distortion in the projector, which makes the projected sinusoidal fringe patterns non-sinusoidal. In order to address this issue, a generic gamma non-linearity model based on constant-intensity images is proposed in this paper. In the proposed model, system defocus and noise are considered and analysed. It is demonstrated through theoretical derivation that the constant-intensity images remain unchanged, with no additional frequency being produced. For this reason, system defocus is not modelled in the proposed gamma calibration model and the related defocus parameters need not be calculated, which reduces the complexity of the calculation. Any noise that exists in the optical measurement system is another main factor influencing the greyscale levels of the image. A mutual information (MI)-based denoising method is proposed to reduce the noise and improve the accuracy of the gamma calibration. Furthermore, with the defocus analysis and the noise reducing method, a robust pixel-wise gamma calibration method is introduced. The experimental results in this paper show that the proposed gamma calibration method is able to accurately calibrate the gamma non-linearity of the system. Moreover, the phase precision is significantly improved and a higher quality measurement is achieved for the measured surfaces. [ABSTRACT FROM AUTHOR]

Plasma sheath poses a serious challenge to inverse synthetic aperture radar (ISAR) imaging of hypersonic targets. This paper investigated the distribution characteristics of the electron density and velocity field in the plasma sheath surrounding the hypersonic target in various flight scenes. The incident depth and reflective surface of electromagnetic (EM) waves with X-band, Ku-band, and Ka-band can be determined based on the plasma frequency. We established the echo model coupled with the velocity field of the plasma sheath on the reflective surface and obtained one-dimensional range profiles and ISAR images of the hypersonic target in various flight scenes. The simulation results indicated that the non-uniform velocity field on the reflective surface induced displacement and diffusion in the one-dimensional range profile, resulting in ISAR image distortion. A changing flight scene and radar frequency can have an impact on imaging results. Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) were utilized to assess the impact of plasma sheath on ISAR images. This study revealed the defocus mechanism of the ISAR image caused by the velocity field of the plasma sheath and provided a theoretical reference for the selection of radar frequency for hypersonic targets in various flight scenes. [ABSTRACT FROM AUTHOR]

Different from the object motion blur, the defocus blur is caused by the limitation of the cameras’ depth of field. The defocus amount can be characterized by the parameter of point spread function and thus forms a defocus map. In this paper, we propose a new network architecture called Defocus Image Deblurring Auxiliary Learning Net (DID-ANet), which is specifically designed for single image defocus deblurring by using defocus map estimation as auxiliary task to improve the deblurring result. To facilitate the training of the network, we build a novel and large-scale dataset for single image defocus deblurring, which contains the defocus images, the defocus maps and the all-sharp images. To the best of our knowledge, the new dataset is the first large-scale defocus deblurring dataset for training deep networks. Moreover, the experimental results demonstrate that the proposed DID-ANet outperforms the state-of-the-art methods for both tasks of defocus image deblurring and defocus map estimation, both quantitatively and qualitatively. The dataset, code, and model is available on GitHub: https://github.com/xytmhy/DID-ANet-Defocus-Deblurring. [ABSTRACT FROM AUTHOR]

Due to limited depth-of-field of digital single-lens reflex cameras, the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred (out-of-focus) in the image. Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene. In this paper, a new Fuzzy Based Hybrid Focus Measure (FBHFM) for multi-focus image fusion has been proposed. Optimal block size is very critical step for multi-focus image fusion. Particle Swarm Optimization (PSO) algorithm has been used to find optimal size of the block of the images for extraction of focus measure features. After finding optimal blocks, three focus measures Sum of Modified Laplacian, Gray Level Variance and Contrast Visibility has been extracted and combined these focus measures by using intelligent fuzzy technique. Fuzzy based hybrid intelligent focus values were estimated using contrast visibility measure to generate focused image. Different sets of multi-focus images have been used in detailed experimentation and compared the results with state-of-the-art existing techniques such as Genetic Algorithm (GA), Principal Component Analysis (PCA), Laplacian Pyramid discrete wavelet transform (DWT), and aDWT for image fusion. It has been found that proposed method performs well as compare to existing methods. [ABSTRACT FROM AUTHOR]

Depth of focus is the major contributor to lithographic process margin. One of the major causes of focus variation is imperfect planarization of fabrication layers. Presently, optical proximity correction (OPC) methods are oblivious to the predictable nature of focus variation arising from wafer topography. As a result, designers suffer from manufacturing yield loss as well as loss of design quality through unnecessary guardbanding. In this paper, the authors propose a novel flow and method to drive OPC with a topography map of the layout that is generated by chemical-mechanical polishing simulation. The wafer topography variations result in local defocus, which the authors explicitly model in the OPC insertion and verification flows. In addition, a novel topography-aware optical rule check to validate the quality of result of OPC for a given topography is presented. The experimental validation in this paper uses simulation-based experiments with 90-nm foundry libraries and industry-strength OPC and scattering bar recipes. It is found that the proposed topography-aware OPC (TOPC) can yield up to 67% reduction in edge placement errors. TOPC achieves up to 72% reduction in worst case printability with little increase in data volume and OPC runtime. The electrical impact of the proposed TOPC method is investigated. The results show that TOPC can significantly reduce timing uncertainty in addition to process variation. [ABSTRACT FROM AUTHOR]

Camera parameters can't be estimated accurately using traditional calibration methods if the camera is substantially defocused. To tackle this problem, an improved approach based on three phase-shifting circular grating (PCG) arrays is proposed in this paper. Rather than encoding the feature points into the intensity, the proposed method encodes the feature points into the phase distribution, which can be recovered precisely using phase-shifting methods. The PCG centers are extracted as feature points, which can be located accurately even if the images are severely blurred. Unlike the previous method which just uses a single circle, the proposed method uses a concentric circle to estimate the PCG center, such that the center can be located precisely. This paper also presents a sorting algorithm for the detected feature points automatically. Experiments with both synthetic and real images were carried out to validate the performance of the method. And the results show that the superiority of PCG arrays compared with the concentric circle array even under severe defocus. [ABSTRACT FROM AUTHOR]

In this paper, we tackle depth estimation and blur removal from a single out-of-focus image. Previously, depth is estimated, and blurred is removed using multiple images; for example, from multiview or stereo scenes, but doing so with a single image is challenging. Earlier works of monocular images for depth estimated and deblurring either exploited geometric characteristics or priors using hand-crafted features. Lately, there is enough evidence that deep convolutional neural networks (CNN) significantly improved numerous vision applications; hence, in this article, we present a depth estimation method that leverages rich representations learned from cascaded convolutional and fully connected neural networks operating on a patch-pooled set of feature maps. Furthermore, from this depth, we computationally reconstruct an all-focus image, i.e., removing the blur and achieve synthetic re-focusing, all from a single image. Our method is fast, and it substantially improves depth accuracy over the state-of-the-art alternatives. Our proposed depth estimation approach can be utilized for everyday scenes without any geometric priors or extra information. Furthermore, our experiments on two benchmark datasets consist images of indoor and outdoor scenes, i.e., Make3D and NYU-v2 demonstrate superior performance in comparison with other available depth estimation state-of-the-art methods by reducing the root-mean-squared error by 57% and 46%, and state-of-the-art blur removal methods by 0.36 dB and 0.72 dB in PSNR, respectively. This improvement in-depth estimation and deblurring is further demonstrated by the superior performance using real defocus images against images captured with a prototype lens. [ABSTRACT FROM AUTHOR]

This paper proposes the first application of a split-range control technique on a concentrating solar collector to improve an absorption plant production. Solar absorption plants have solar power availability in phase with cooling demand under design conditions. Thus, it is a powerful cooling technology in the context of renewable energy and energy efficiency. These plants need control systems to cope with solar irradiance intermittency, reject irradiation disturbances, manage fossil fuels backup systems and dump closed-loop thermal-hydraulic oscillations. In this work, control techniques are proposed and simulated in an absorption plant in Spain. The plant consists of a concentrating Fresnel solar collector connected to an absorption chiller. The objectives are to operate with 100% renewable solar energy and avoid safety defocus events while reducing temperature oscillations and control actuators effort. Firstly, the current available plant controllers are defined, then two modifications are proposed. The first modification is a split-range controller capable of manipulating both flow and defocus of the Fresnel collector, the second modification is a PI controller to substitute the original chiller on-off controller. The results compare, through validated models, the different control systems and indicate that using both proposed controllers reduces 94% of the sum of actuators effort and 43% of the integral of absolute set-point tracking error compared to the plant's factory pre-set controllers. The suggested controllers increase 66% of energy production and 63% of exergy production. Besides, the split-range technique can be extended to any concentrating solar collector control. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper proposes a method for displaying images at the fovea of the retina taking visual acuity into account. Previous research has shown that a point light source projected onto the retina forms an ellipse, which can be computed with wavefront tracing from each point in space. We propose a novel concept using conoid tracing, with which we can acquire defocusing information several times faster than that acquired by previous methods. We also show that conoid tracing is more robust and produces higher quality results. In conoid tracing the ray is regarded as a conoid, a thin cone-like shape with varying elliptical cross-section. The viewing ray from the retina is traced as a conoid and evaluated at each sample location. Using the sampled and pre-computed data for the spatial distribution of blurring, we implemented an interactive eyeglass simulator. This paper demonstrates some visualization results utilizing the interactivity of the simulator, which an eyeglass lens design company uses to evaluate the design of complex progressive lenses. [ABSTRACT FROM AUTHOR]

As advanced technologies in wafer manufacturing push patterning processes toward lower k1 subwavelength printing, lithography for mass production potentially suffers from decreased patterning fidelity. This results in the generation of many hotspots, which are actual device patterns with relatively large critical-dimension and image errors with respect to on-wafer targets. Hotspots can be formed under a variety of conditions such as the original design being unfriendly to the resolution enhancement technique that is applied, unanticipated pattern combinations in rule-based optical proximity correction (OPC), or inaccuracies in model-based OPC. When these hotspots fall on locations that are critical to the electrical performance of a device, device performance and parametric yield can be significantly degraded. The golden verification signoff tool using a simulation-based approach has occupied the mainstream and has been able to accurately detect hotspots. However, this approach represents a runtime-quality tradeoff point that is high in quality but also high in runtime. There is also little point in trying to replace the golden signoff tool. We are motivated to develop a low-runtime "prefilter" that reduces the amount of layout area to be analyzed by the golden tool, without compromising the overall quality of hotspot finding. In this paper, we first describe a novel detection algorithm for hotspots induced by lithographic uncertainty. Our goal is to rapidly detect all lithographic hotspots without significant accuracy degradation. In other words, we propose a filtering method: as long as,there are no "false negatives," i.e., we reliably obtain a superset of actual hotspots, then our method can dramatically reduce the layout area processed by golden hotspot analysis. Our hotspot detection algorithm includes layout graph construction, graph planarization, three-level bridging hotspot detection, and necking hotspot detection. We have tested our flow on several industry test cases. The experimental results show that our method is promising: for benchmark designs in 90-nm and 65-nm technologies, 100% of bridging and open hotspots are detected with few falsely detected hotspots. The average runtime of our method is more than 496× faster compared to the commercial tool. [ABSTRACT FROM AUTHOR]

Subresolution assist feature (SRAF) and etch-dummy insertion techniques have been absolutely essential for process window enhancement and CD control in photo and etch processes. However, as focus levels change during lithography manufacturing, CDs at a given "legal" pitch can fail to achieve manufacturing tolerances. Placed standard-cell layouts may not have the ideal whitespace distribution to allow for an optimal assist-feature insertion. This paper first describes a novel dynamic programming-based technique for Assist-Feature Correctness (AFCorr) in detailed placement of standard-cell designs. At the same time, etch-dummy features are used in the mask data preparation flow to reduce CD skew between resist and etch processes and to improve the printability of layouts. However, etch-dummy rules conflict with the SRAF insertion because each of the two techniques requires specific design rules. We further present a novel SRAF-aware etch-dummy insertion method (SAEDM) which optimizes the etch-dummy insertion to make the layout more conducive to the assist-feature insertion after the etch-dummy features have been inserted. Since placement of cells can create forbidden-pitch violations of resist process and can increase etch skew, the placer must also generate etch- dummy-correct placement. This can be solved by Etch-dummy Correctness (EtchCorr), which is an intelligent whitespace management for etch-dummy-corrected placement, an extension of the AFCorr methodology. These methods for enhanced resist and etch CD control are validated on industrial test cases with respect to wafer printability, database complexity, and device performance. For benchmark designs, we validate the four methodologies: 1) AFCorr; 2) SAEDM; 3) AFCorr + SAEDM; and 4) AFCorr + EtchCorr + SAEDM. The AFCorr placement perturbation achieves a significant reduction in forbidden pitches between polysilicon shapes. Using 1) flow, forbidden-pitch count of photo process is reduced by 76%-100% for 130 nm and by 87%-100% for 90 nm. Our novel Corr design-perturbation technique, which combines the AFCorr and EtchCorr methods, facilitates additional SRAF and etch-dummy insertions and, thus, reduces the CD skew between the photo and etch processes. After Corr with SAEDM, edge placement error (EPE) count is also reduced by 91%-100% in the resist CD and by 72%-98% in the etch CD. Our methods provide a substantial improvement in CD control with negligible timing, area, and CPU overhead. The advantages of such correctness methods are expected to increase in future technology nodes. [ABSTRACT FROM AUTHOR]

In order to develop security systems for identity authentication, face recognition (FR) technology has been applied. One of the main problems of applying FR technology is that the systems are especially vulnerable to attacks with spoofing faces (e.g., 2D pictures). To defend from these attacks and to enhance the reliability of FR systems, many anti-spoofing approaches have been recently developed. In this paper, we propose a method for face liveness detection using the effect of defocus. From two images sequentially taken at different focuses, three features, focus, power histogram and gradient location and orientation histogram (GLOH), are extracted. Afterwards, we detect forged faces through the feature-level fusion approach. For reliable performance verification, we develop two databases with a handheld digital camera and a webcam. The proposed method achieves a 3.29% half total error rate (HTER) at a given depth of field (DoF) and can be extended to camera-equipped devices, like smartphones. [ABSTRACT FROM AUTHOR]

This article discusses a depth prediction model that takes advantage of rich interpretations. Profundity assessment is a basic interest for scene understanding and exact 3D reproduction. Latest methodologies with profound learning exploit mathematical designs of standard sharp pictures to foresee profundity maps. In any case, cameras can likewise deliver pictures with defocus obscure contingent upon the profundity of the articles and camera settings. Subsequently, these highlights might address a significant clue for figuring out how to foresee profundity. In this article, we postulate a full framework for single-picture profundity expectation by estimating the level of obscure w.r.t real profundity by bringing the picture in to concentrate just on pre-characterized focal point numbers. As a result, these characteristics may provide a crucial clue for studying to predict depth. These lens numbers indicate the distance at which the lens is currently focused. We also intend to know the influence of lens aperture numbers on the depth estimated. For this stated goal,We introduce a new data set that has 477 images taken in real-time using a DSLR (Digital Single-Lens Reflex). For indoor pictures, a lens is coupled with ground truth depth data provided with a laser distance meter.On this new platform, the strategy has been a framework that supports new data set and is proved that the predicted depth estimates correlate with ground truth by 98.7 percent with an 8.647 Std Error estimate. When compared to recent research on stereo vision and other non-triangulation techniques proposed so far, the depth estimations derived from the proposed model approximates the ground truth with RMSE of 0.05 and display around 98.7 percent correlation wrt ground truth data. Depth estimation strategy using a Single RGB cameras are proved efficient in computing depth estimates from blur with 99 percent accuracy, which is not in an earlier case. Our proposed model evidently works well with both sharp and blur images in computing depth estimates up to 3.3 meters range irrespective of whether an image is in focus or out of focus. [ABSTRACT FROM AUTHOR]

Highlights • Our method can calibrate the out-of-focus camera effectively. • The pattern contains three gratings simplify the calibration target for defocusing calibration. • The entire process requires no metric measurement of the test pattern. • The method can be applied in long-range vision systems for it can reduce the size of calibration target. Abstract Conventional camera calibrations with circular patterns always require sharp target images and thus fail if the images are blurred. In this paper, we present an effective calibration approach using three circular gratings, which can be employed in defocus scene. Rather than using the concentric circles as the targets, the proposed method utilizes circular gratings generated by phase-shifting methods. The intrinsic parameters of the camera can be obtained with the images of circular points, and it works even if the camera is out-of-focus. Numerical simulation and real data experiments have been carried out to validate the method. And the results show that our method can calibrate the camera effectively even under severe defocus. Moreover, the entire process requires no metric measurement of the test pattern, which is very flexible to implement and suitable for people who are not familiar with computer vision. [ABSTRACT FROM AUTHOR]

A new depth estimation method for 3D reconstruction in a synthetic aperture integral imaging framework is presented. This method removes the edges of the objects in the elemental images when the objects are in focus. This strategy aims to compensate for the noise that objects focused close to the cameras can introduce into the photo-consistency measure of objects at higher depths. Furthermore, a photo-consistency criterion is applied combining a defocus and a correspondence measure, and a depth regularization method which smooths noisy depth results for the case of object surfaces. The proposed method obtains consistent results for any type of object surfaces as well as very sharp boundaries. Experimental results show that our method reduces the noise in the object edges and gives rise to an improvement in the depth map results in relation to the other methods shown in the comparative analysis. [ABSTRACT FROM AUTHOR]

This paper reports on the modeling of arrayed-waveguide gratings (AWGs) by means of Fourier optics where the coupling between the grating waveguides and defocus of the star couplers is taken into account as well. Special interest is drawn to the geometrical modeling of AWGs. The paraxial approximation for the free-space propagation within the star couplers, the exact calculation of the coupling coefficients for the star couplers by an orthonormal basis (ONB) expansion, and the drawbacks due to the nonunitary transfer matrix provided by the Green's functions approach for the coupling between the grating waveguides, as well as possible improvements thereof, are identified as crucial points. An efficient orthonormalization procedure by means of an eigenvector decomposition is presented. A unitary approximation of the transfer matrix, which is in itself approximate but in general not unitary, introduced within the impulse response method, is obtained. The presented simulation technique allows for ab initio simulations, which do not fall back on any experimental input, for the spectral response of AWGs, which are found in good agreement with experimental results. [ABSTRACT FROM PUBLISHER]

An optical imaging system's image quality can deteriorate due to uncorrected astigmatism and defocus. An approach to correct these issues is proposed, which involves a non-mechanical, electronically adjustable system. This system consists of three liquid crystal-based cylindrical lenses, which adjust optical power depending on applied voltage values. The advantages of this system include a simple and low-cost structure, large aperture size, low-voltage drive, and compact design. This non-mechanical solution has great potential for various applications, such as wavefront correction for large telescopes, microscopy, augmented reality/virtual reality, and prescription eyeglasses. Design, fabrication, and optical characterization of the proposed device are discussed. [ABSTRACT FROM AUTHOR]

To clarify the influence of laser power density on the stability of laser welding 5083 Al alloy with 5183 Al alloy filler wire, experiments with different laser powers and levels of defocus, which are related to laser density, were carried out. A high speed camera, appearance inspection and macroscopic metallography were used to analyse the effects of laser power and defocus on the stability of welding wire melting, droplet transfer, molten pool fluctuation and weld solidification. The results showed that a small curvature curl would appear at the end of the wire if the laser power could evaporate the wire instantly. A large curvature curl would occur in the low power of the laser beam, which is too small to melt the wire. The droplet transition mode has gone through three stages of droplet transition liquid bridge transition-droplet transition, as the laser power was changed from 1600 to 2000 W, or the focus changed from -9 to +15 mm. Compared to the defocus, the laser power has a greater effect on the power density and the stability of the laser welding with filler wire. The droplet transition would occur when the diameter of the droplet exceeded the diameter of the wire. The weld metal surface had irregular flat areas periodically, while it was smooth during the liquid bridge transition. The violently fluctuating molten pool, splashes and holes would be appeared in the weld seam, when the molten pool had a high power density; however, when the molten pool had a low power density, asymmetric weld reinforcement would be found due to the small volume pool. [ABSTRACT FROM AUTHOR]

In tunnel boring machine construction sites, on-site calibration of large field-of-view binocular cameras is still a challenging task due to factors such as the narrow spaces of the machines' mechanical structures, high pressure, or falling rocks. Therefore, a calibration method using a small plate in proximity to the camera (a defocused position safe for workers) is proposed in this paper to deal with the above challenges. First, a defocus-insensitive feature point encoding pattern is developed. Then feature points are extracted through a phase recovery network based on the Swin Transformer, and finally camera parameters are optimized based on virtual symmetric transfer errors. The relevant simulation and experimental data show that the relative error between the proposed method and the phase-shift method in feature extraction is 0.15 pixels, while the relative error between the proposed method and a high-precision laser tracker in three-dimensional measurement is 1.3%. The results demonstrate the feasibility of the method in a large field-of-view binocular camera for tunnel boring machine construction sites. Increasing the diversity of data sets and lightweight models will be the focus of future research. • Feature point encoding using a defocus-insensitive global coordinate encoder. • Proposed PRT network to recover the phase information of feature points. • Optimization of camera parameters using a virtual symmetric transfer error. [ABSTRACT FROM AUTHOR]

Microscopic cell image analysis is indispensable to cell biology. Images of cells can easily degrade due to optical diffraction or focus shift, as this results in low signal-to-noise ratio (SNR) and poor image quality, hence affecting the accuracy of cell analysis and identification. For a quantitative analysis of cell images, restoring blurred images to improve the SNR is the first step. A parameter estimation method for defocused microscopic cell images based on the power law properties of the power spectrum of cell images is proposed. The circular radon transform (CRT) is used to identify the zero-mode of the power spectrum. The parameter of the CRT curve is initially estimated by an improved differential evolution algorithm. Following this, the parameters are optimized through the gradient descent method. Using synthetic experiments, it was confirmed that the proposed method effectively increased the peak SNR (PSNR) of the recovered images with high accuracy. Furthermore, experimental results involving actual microscopic cell images verified that the superiority of the proposed parameter estimation method for blurred microscopic cell images other method in terms of qualitative visual sense as well as quantitative gradient and PSNR. [ABSTRACT FROM AUTHOR]

• The physical interpretation of defocused speckle imaging is highlighted. • Speckle field sampling distance can be easily controlled by adjusting camera focus. • The correspondence between defocused and objective speckle patterns is experimentally demonstrated. • Simultaneous multi-axial object motions are identified using a dual-camera arrangement. • Remote measurements are demonstrated at various distances up to 16 m. When an object with a rough surface is illuminated using a coherent laser, the scattered light rays interfere to create a three-dimensional speckle field that fills the adjacent space. If the object is displaced or tilted, the entire speckle field moves in response. Therefore, the motion of an object can be measured remotely by tracking the movements of the objective speckle pattern recorded on a lensless imaging sensor placed within the speckle field. It is demonstrated that the same image acquisition can be made using a defocused camera, where the recorded speckle pattern corresponds to the image that would be recorded by a lensless sensor placed at the camera's focal plane. In this paper, this feature is experimentally demonstrated by showing the correspondence between the captured objective and defocused speckle patterns. The effective speckle field sampling position can then be freely chosen by controlling the camera focus distance, rather than needing to move the sensor physically. Furthermore, the defocused speckle patterns are scaled by the optical system in-focus magnification ratio, enabling further tuning of measurement sensitivity. This paper presents a series of displacement and tilt measurements designed to investigate the sensitivity characteristics of defocused speckle imaging. The measurements made at various object distances up to 16 m demonstrate the method's suitability for high-sensitivity remote measurement applications. A strategy to separate linear and rotational components under multiaxial object motion is also proposed. [ABSTRACT FROM AUTHOR]

In this paper, attempts have been made to study the joint effects of apodization and aperture masking on the diffraction images of coherently illuminated straight edge. The Edge-Ringing, Edge-Shift and Edge-Eradient of the edge images have been evaluated for different values of apo-dization using edge masking of circular apertures. We have considered rotationally symmetric, ab-errated coherent optical system. These investigations have lead to the use of certain pupil functions in conjunction with optimal apodizers to assess the quality of edge images. Any obstruction placed in the light path of an optical system prevents waves from a portion of the wavefront in reaching the focal zone. This results in the change in the light flux at every point of the diffraction pattern. This is in turn, depends on the shape and size of the obstruction.

• A flexible calibration method for defocused cameras is proposed. • The method has not only good calibration accuracy but also high operability. • The image pair is used to realize the linear camera calibration. • The image distance conversion model is built to decouple intermediate parameters. Complex engineering scenes increase the difficulty of camera calibration. High precision and easy operation are the necessary conditions to ensure successful calibration. This paper proposes a flexible calibration method for defocused cameras. Firstly, the initial calibration is completed by traditional Zhang's method. Then, the linear camera calibration based on the image pair is carried out. The image pair is obtained when the lens focuses on the calibration and measuring positions in sequence on the premise of keeping the calibration target stationary. The distortion coefficient is solved independently, the image distance conversion model is established to decouple the intermediate parameters, and finally, the linear solution of the camera parameters is obtained. The proposed method can complete the entire calibration process for a large-range vision measurement system using a small planar target. The number of calibration images required is close to Zhang's method. There is no need to fix the calibration target under multiple attitudes separately, which has strong operability. Experimental results show that the method is effective. The maximum calibration error of intrinsic parameters is 1.29%, and the maximum mean reprojection error is only 0.127 pixels. In addition, this method has good anti-noise performance and has satisfactory calibration accuracy under the action of different influencing factors, which indicates its broad applicability. The method can be applied to calibrating defocused cameras in special scenes such as engineering sites. [ABSTRACT FROM AUTHOR]

The main effect of temperature change on infrared imaging system is the focus shift of infrared lenses. This paper analyzes the equivalent influence on imaging between the temperature change and the defocus at room temperature. In order to quantify the equivalence, we define an equivalent thermal defocus amount (ETDA). The ETDA describes the distance of the photosensitive surface shifting at room temperature, which has the same effect on imaging as the temperature changes. To model the ETDA, the expression of the focal shift as a function of temperature is obtained by solving partial differential equations for the thermal effect on light path firstly with some approximations. Then point spread functions of the thermal effect and defocus at room temperature are modeled based on wave aberration. The calculating model of ETDA is finally established by making their PSFs equal under the condition that the cutoff frequency of infrared imaging systems is much smaller than that of infrared lens. The experimental results indicate that defocus of ETDA at room temperature has the same influence on imaging as the thermal effect. Prospectively, experiments at high/low temperature can be replaced by experiments at room temperature with ETDA. [ABSTRACT FROM AUTHOR]

The multi-slice integration (MSI) method is one of the approachs to extend the depth of view (DOV) of the pulsed laser range-gated imaging (PLRGI) system. When the DOV is large enough and exceeds the depth of focus of the system, it may make some targets in the image clear and others blurred. In addition, forward scatter is also considered to have a blurring effect on the image. There is very little literature to solve the combined effect of forward scatter and defocus. An imaging model is built based on the model from Jaffe–McGlamery and Fourier optics. According to the imaging model, backscattered light is independent from reflected light from the target, and forward scatter has a relationship with the reflected light. Thus, backscattered light should be removed before deblurring. First, rolling ball and intensity transformation are used to remove the backscattered light and enhance the image. Then, a deep learning model based on Transformer is used to deblur the image. To enable the deep learning model to accommodate different degrees of blurred image, 16 different blur kernels are generated according to the imaging model. Sharp images from a DPDD dataset were chosen to train the model. Images of varying degrees of blur were collected from a water tank and a boat tank by the PLRGI system as test sets. Image deblurring results show that the proposed method can remove different levels of blur and can deal with images which have sharp targets and blurred targets together. [ABSTRACT FROM AUTHOR]

Classical image segmentation techniques in computer vision exploit visual cues such as image edges, lines, color and texture. Due to the complexity of real scenarios, the main challenge is achieving meaningful segmentation of the imaged scene since real objects have substantial discontinuities in these visual cues. In this paper, a new focus-based perceptual cue is introduced: the focus signal . The focus signal captures the variations of the focus level of every image pixel as a function of time and is directly related to the geometry of the scene. In a practical application, a sequence of images corresponding to an autofocus sequence is processed in order to infer geometric information of the imaged scene using the focus signal. This information is integrated with the segmentation obtained using classical cues, such as color and texture, in order to yield an improved scene segmentation. Experiments have been performed using different off-the-shelf cameras including a webcam, a compact digital photography camera and a surveillance camera. Obtained results using Dice’s similarity coefficient and the pixel labeling error show that a significant improvement in the final segmentation can be achieved by incorporating the information obtained from the focus signal in the segmentation process. [ABSTRACT FROM AUTHOR]

• An analytical solution to predict the curvature and deflection of a thermally actuated deformable mirror with compression bias was presented. • The effect of the material properties and different assembling conditions on the final deformed configuration were taken into account. The proposed formulation was compared to numerical analysis and experimental evidences, showing a good correlation with respect to all the considered deformation and stresses parameters. • The analytic formulation opens up the possibility of multiobjective optimization of these adaptive optical systems. Interference-fit joints are typically adopted to produce permanent assemblies among mechanical parts. The resulting contact pressure is generally used for element fixing or to allow load transmission. Nevertheless, some special designs take advantage of the contact pressure to induce desiderata deformation or to mitigate the stress field inside the structure. Biased interference fitting between a planar mirror and an external ring could be used to induce the required curvature to realize new adaptive lens for optical aberration correction. Recently, thermally-actuated deformable mirror on this principle based, was proposed and prototyped. Although the feasibility and utility of such innovative lens was demonstrated, no comprehensive theory was developed to describe mirror behavior and predict their curvature. Nowadays, the use of approximated numerical approach, such as the finite element method, is the only way to study the interaction between biased and interference fitted bodies. The paper aims to give the theoretical background for the correct design of adaptive lens actuated by interference fitting. A new formulation for the curvature prediction is proposed and compared with finite element analysis and available experimental measurements. [Display omitted] [ABSTRACT FROM AUTHOR]

• A convolutional neural network (Phase-Net) is built for phase extraction of calibration pattern. • A dataset generation method is designed to train the Phase-Net. • The eccentricity error of circular pattern in projective geometry is shown and corrected. • An experiment is carried out to analyze the influence of lens parameters and working distance on the feature extraction accuracy and calibration results of phase-Net. Camera calibration is difficult when the focus plane is in a dangerous place or where people are not easy to reach. Therefore, this paper proposes a calibration method which can be used in the out-of-focus area of the camera. Firstly, a circular calibration pattern based on phase coding is made. Next, a deep learning-based phase recovery network (Phase-Net) is built, and then the recovered phase diagram is corrected for ellipse eccentricity to obtain the feature points needed for camera calibration. The proposed method only needs one shot to recover the phase, which overcomes the problem that the defocusing calibration method based on the phase shift principle needs multiple patterns to recover the phase. Simulation and experiments demonstrate that the maximum mean reprojection error is 0.11 pixels, and the relative error between the calibration results of this method and phase-shifting method is 1.54%. The obtained results validate the effectiveness of Phase-Net in engineering applications. [ABSTRACT FROM AUTHOR]

Defocus is an important factor that causes image quality degradation of optoelectronic tracking equipment in the shooting range. In this paper, an improved blind/referenceless image spatial quality evaluator (BRISQUE) algorithm is formulated by using the image characteristic extraction technology to obtain a characteristic vector (CV). The CV consists of 36 characteristic values that can effectively reflect the defocusing condition of the corresponding image. The image is evaluated and scored subjectively by the human eyes. The subjective evaluation scores and CVs constitute a set of training data samples for the defocusing evaluation model. An image database that contains sufficiently many training samples is constructed. The training model is trained to obtain the support vector machine (SVM) model by using the regression function of the SVM. In the experiments, the BRISQUE algorithm is used to obtain the image feature vector. The method of establishing the image definition evaluation model via SVM is feasible and yields higher subjective and objective consistency.

Abstract: Reconstructed exit waves are useful to quantify unknown structure parameters such as the position and composition of the atom columns at atomic scale. Existing techniques provide a complex wave in a flat plane which is close to the plane where the electrons leave the atom columns. However, due to local deviation in the flatness of the exit surface, there will be an offset between the plane of reconstruction and the actual exit of a specific atom column. Using the channelling theory, it has been shown that this defocus offset can in principle be determined atom column-by-atom column. As such, the surface roughness could be quantified at atomic scale. However, the outcome strongly depends on the initial plane of reconstruction especially in a crystalline structure. If this plane is further away from the true exit, the waves of the atom columns become delocalized and interfere mutually which strongly complicates the interpretation of the exit wave in terms of the local structure. In this paper, we will study the delocalization with defocus using the channelling theory in a more systematic way. [Copyright &y& Elsevier]

The apochromatic triplet insures a good correction of chromatic aberrations and second spectrum. The traditional design methods concentrate only over these aims. The geometrical aberrations are not under control, so that, the spherical one, especially is present in a large amount. These considerations limit the aperture to slow speed numbers (f/8…f/10). The new methods of analysis based on Fourier optics allow substantial improvement regarding more subtle characteristics, such as contrast, resolution and cut off frequency. The paper shows that the solutions given by the traditional design present poor characteristics diffraction determined. Slight defocusing aiming. minimum spot size on- axis or minimum RMS OPD on-axis can improve the system's quality close to the diffraction limited one. [ABSTRACT FROM AUTHOR]

In the field of 3D measurement, digital fringe projection (DFP) techniques have become a hotspot of research and application due to its non-contact, low cost and high resolution characteristics, but the gamma effect caused by projector seriously affects the 3D measurement quality of DFP techniques. This paper presents a Tabu Search optimization algorithm to generate high-quality binary patterns, which are projected and defocused to obtain the wrap phase, which can avoid the influence of gamma effect on phase quality. Secondly, in order to solve the problem that it is difficult to maintain the degree of defocus, a defocus adaptive optimization system is built. Finally, in order to reduce the influence of projector defocus on Gray code phase unwrapping, a combined Gray code method is proposed, which can accurately unwrap the wrap phase and reduce the interference of the color of object on phase unwrapping. The experimental results show that the proposed method improves the 3D measurement results of DFP techniques and improves the robustness.

In transmission electron microscope (TEM), both the amplitude and the phase of electron beam change when electrons traverse a specimen. The amplitude is easily obtained by the square root of the intensity of a TEM image, while the phase affects defocused images. In order to obtain the phase map and verify the theoretical model of the interaction between electron beam and specimen, a lot of simulations have to be performed by researchers. In this work, we have simulated defocus images of a SiC nanowire in TEM with the method of electron optics. Mean inner potential and charge distribution on the nanowire have been considered in the simulation. Besides, due to electron scattering, coherence loss of the electron beam has been introduced. A dynamic process with Bayesian optimization was used in the simulation. With the infocus image as input and by adjusting fitting parameters, the defocus image is determined with a reasonable charge distribution. The calculated defocus images are in a good agreement with the experimental ones. Here, we present a complete solution and verification method for solving nanoscale charge distribution in TEM. [ABSTRACT FROM AUTHOR]

Plasma sheath poses a serious challenge to inverse synthetic aperture radar (ISAR) imaging of hypersonic targets. This paper investigated the distribution characteristics of the electron density and velocity field in the plasma sheath surrounding the hypersonic target in various flight scenes. The incident depth and reflective surface of electromagnetic (EM) waves with X-band, Ku-band, and Ka-band can be determined based on the plasma frequency. We established the echo model coupled with the velocity field of the plasma sheath on the reflective surface and obtained one-dimensional range profiles and ISAR images of the hypersonic target in various flight scenes. The simulation results indicated that the non-uniform velocity field on the reflective surface induced displacement and diffusion in the one-dimensional range profile, resulting in ISAR image distortion. A changing flight scene and radar frequency can have an impact on imaging results. Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) were utilized to assess the impact of plasma sheath on ISAR images. This study revealed the defocus mechanism of the ISAR image caused by the velocity field of the plasma sheath and provided a theoretical reference for the selection of radar frequency for hypersonic targets in various flight scenes.