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In the paper, there is analyzed the signal quality assessment method based on delay tap asynchronous sampling, both for binary and multilevel PAM signals. The obtained multilevel phase diagrams are far more complicated than binary ones. The phase diagrams are affected by the signal distortions but it is difficult to relate reliably the phase diagram form to the distortion type and its influence on the signal quality.

In this paper, we study how to compactly represent image’s characteristics for fast image retrieval. We propose supervised rotation invariant compact discriminative binary descriptors through combining convolutional neural network with hashing. In the proposed network, binary codes are learned by employing a hidden layer for representing latent concepts that dominate on class labels. A loss function is proposed to minimize the difference between binary descriptors that describe reference image and the rotated one. Compared with some other supervised methods, the proposed network doesn’t have to require pair-wised inputs for binary code learning. Experimental results show that our method is effective and achieves state-of-the-art results on the CIFAR-10 and MNIST datasets.

Shadow mapping is commonly used in real-time rendering. In this paper, we presented an accurate and efficient method of soft shadows generation from planar area lights. First this method generated a depth map from light’s view, and analyzed the depth-discontinuities areas as well as shadow boundaries. Then these areas were described as binary values in the texture map called binary light-visibility map, and a parallel convolution filtering algorithm based on GPU was enforced to smooth out the boundaries with a box filter. Experiments show that our algorithm is an effective shadow map based method that produces perceptually accurate soft shadows in real time with more details of shadow boundaries compared with the previous works.

In the paper we investigate the possibility of color reconstructions of holograms with a single DMD and incoherent LED source illumination. Holographic display is built with 4F imaging system centering reconstruction volume around the DMD surface. The display design employs complex coding scheme, which allows reconstructing complex wave from a binary hologram. In order to improve the quality of reconstructed holograms time multiplexing method is used. During the optical reconstructions we analyze quality of reconstructed holograms with incoherent RGB light sources as a function of reconstruction distance, present the possibility of 3D hologram reconstruction, and investigate temporal coherence effects in holographic display with the DMD.

The recent proposed Indexing-First-One (IFO) hashing is a latest technique that is particularly adopted for eye iris template protection, i.e. IrisCode. However, IFO employs the measure of Jaccard Similarity (JS) initiated from Min-hashing has yet been adequately discussed. In this paper, we explore the nature of JS in binary domain and further propose a mathematical formulation to generalize the usage of JS, which is subsequently verified by using CASIA v3-Interval iris database. Our study reveals that JS applied in IFO hashing is a generalized version in measure two input objects with respect to Min-Hashing where the coefficient of JS is equal to one. With this understanding, IFO hashing can propagate the useful properties of Min-hashing, i.e. similarity preservation, thus favorable for similarity searching or recognition in binary space.

Phase-shifting profilometry using binary patterns with projector defocusing has been widely used for high-speed 3D measurement. Recently, a ternary Gray-code based phase unwrapping method has been proposed, which enables to accurately unwrap the phase but reduces the required binary patterns. This paper presents a comparison between the ternary and the traditional binary Gray code-based phase unwrapping methods. NRF (Natl Research Foundation, S’pore) Published version

To avoid high bandwidth detector, fast speed A/D converter, and large size memory disk, a compressive full waveform LIDAR system, which uses a temporally modulated laser instead of a pulsed laser, is studied in this paper. Full waveform data from NEON (National Ecological Observatory Network) are used. Random binary patterns are used to modulate the source. To achieve 0.15 m ranging resolution, a 100 MSPS A/D converter is assumed to make measurements. SPIRAL algorithm with canonical basis is employed when Poisson noise is considered in the low illuminated condition.

We introduce maximum-SINR, sparse-binary waveforms that modulate data information symbols over the entire continuum of the available/device-accessible spectrum. We present an optimal algorithm that designs the proposed waveforms by maximizing the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum- SINR linear filter at the receiver. In addition, we propose a suboptimal, computationally-efficient algorithm. Simulation studies compare the proposed sparse-binary waveforms with their conventional non-sparse binary counterparts and demonstrate their superior SINR performance. The post-filtering SINR and bit-error rate (BER) improvements attained by the proposed waveforms are also experimentally verified in a software-defined radio testbed operating in multipath laboratory environment, in the presence of colored interference.

This paper presents a method to overcome the light spectral range limitation of using digital-light-processing (DLP) projector for 3D shape measurement by developing a mechanical projector. The mechanical projector enables much broader spectral range of light than that the DLP projector allows. The rapidly spinning disk with binary structures can generate desired sinusoidal patterns at a frequency of 10 kHz or higher with a single DC motor. By precisely synchronizing the camera with the projector, phase-shifted fringe patterns can be accurately captured for high-accuracy 3D shape measurement. We further employed a computational framework that could enable absolute phase and thus absolute 3D shape measurement. We developed such prototype system that experimentally demonstrated the success of the proposed method.

The sequence generator generates a sequence of pseudorandom binary numbers using a linear-feedback shift register (LFSR). This block implements LFSR using a simple shift register generator (SSRG, or Fibonacci) configuration. In this article we introduce the concept of probabilistic binary element provides requirements, which ensure compliance with the criterion of "uniformity" in the implementation of the basic physical generators uniformly distributed random number sequences. Based on these studies, we obtained an analytic relation between the parameters of the binary sequence and parameters of a numerical sequence with the shift register output. The received analytical dependencies can help in evaluating the statistical characteristics of the processes in solving problems of statistical modeling. It is supposed that the formation of the binary sequence output from the binary probabilistic element is produced using a physical noise process. It is shown that the observed errors in statistical modeling using pseudo-random numbers do not occur if the model examines linear systems with constant parameters, but in case models of nonlinear systems, higher order moments can have a Gaussian distribution.

In an abnormal cervical cell detection system the discriminated abilities of different features are not same so the optimized combination method of all features is an essential component to this system. Feature selection can improve each feature utilization ratio and the performance of the classification problem. The previous efforts of cervical abnormal cell detection are mainly focused on changing feature space into a new one by using a binary weight vector. In this work, the binary weight values are extended to the multiple weight values. According to the statistical distribution situation of the data, an adaptive margin-based weighted feature selection method is proposed in this paper. This method performs best compared with the other 3 methods. The experimental result achieves 96% accuracy in a real-world cervical smear image dataset.

PURPOSE: In radiation therapy treatment planning systems, structures are represented as parallel 2D contours. For treatment planning algorithms, structures must be converted into labelmap (i.e. 3D image denoting structure inside/outside) representations. This is often done by triangulated a surface from contours, which is converted into a binary labelmap. This surface to binary labelmap conversion can cause large errors in small structures. Binary labelmaps are often represented using one byte per voxel, meaning a large amount of memory is unused. Our goal is to develop a fractional labelmap representation containing non-binary values, allowing more information to be stored in the same amount of memory. METHODS: We implemented an algorithm in 3D Slicer, which converts surfaces to fractional labelmaps by creating 216 binary labelmaps, changing the labelmap origin on each iteration. The binary labelmap values are summed to create the fractional labelmap. In addition, an algorithm is implemented in the SlicerRT toolkit that calculates dose volume histograms (DVH) using fractional labelmaps. RESULTS: We found that with manually segmented RANDO head and neck structures, fractional labelmaps represented structure volume up to 19.07% (average 6.81%) more accurately than binary labelmaps, while occupying the same amount of memory. When compared to baseline DVH from treatment planning software, DVH from fractional labelmaps had agreement acceptance percent (1% ΔD, 1% ΔV) up to 57.46% higher (average 4.33%) than DVH from binary labelmaps. CONCLUSION: Fractional labelmaps promise to be an effective method for structure representation, allowing considerably more information to be stored in the same amount of memory.

Recent developments for laser communication on CubeSats across interplanetary distances will be presented. A binary polarization-shift-keyed modulation scheme using dual gain-switched diode lasers is developed and demonstrated within an end-to-end link testbed to achieve signal acquisition under extremely poor signal-to-noise conditions (-43.5 dB average signal-to-noise power ratio at a 1-MHz symbol rate) to simulate direct-to-Earth links, while simultaneously targeting a limited SWaP footprint (1.5U envelope). Additional system design and constraints for the compact laser transmitter will be discussed.

This paper presents our research findings on high-speed 3D imaging using digital light processing (DLP) technologies. In particular, we compare two different sinusoidal fringe generation techniques using the DLP projection devices: direct projection of 8-bit computer generated sinusoidal patterns (a.k.a, the sinusoidal method), and the creation of sinusoidal patterns by defocusing binary patterns (a.k.a., the binary defocusing method). This paper mainly examines their performance on high-accuracy measurement applications under precisely controlled settings. Two different projection systems were tested in this study: the commercially available inexpensive projector, and the DLP development kit. Experimental results demonstrated that the binary defocusing method always outperforms the sinusoidal method if a sufficient number of phase-shifted fringe patterns can be used.

An optical 3-bit Excess-3 code converter is demonstrated by using Mach-Zehnder Interferometers based on electro-optic effect. It is a way to represent values with a balanced number of positive and negative numbers using a prespecified number N as a biasing value.

We proposed a fully vertical-coupling and one-step etching subwavelength binary blazed grating (BBG) coupler with coupling efficiencies exceeding 80% at a wavelength of 1.55μm. Based on reflector grating and Bragg bottom reflector layer, the coupling efficiency gets its maximum 90% when λ is equal to 1.535μm with the 1 dB wavelength bandwidth is around 35nm. The BBG is formed with multiple rectangular pillars having different widths and uniform height, which is a kind of binary version of the triangular tooth shape of the blazed grating and can be easily fabricated by only one etching step. It is CMOS compatible and available for mass production.

Structured light measurement has been wildly used since 1970s in industrial component detection, reverse engineering, 3D molding, robot navigation, medical and many other fields. In order to satisfy the demand for high speed, high precision and high resolution 3-D measurement for embedded system, a new patterns combining binary and gray coding principle in space are designed and projected onto the object surface orderly. Each pixel corresponds to the designed sequence of gray values in time – domain, which is treated as a feature vector. The unique gray vector is then dimensionally reduced to a scalar which could be used as characteristic information for binocular matching. In this method, the number of projected structured light patterns is reduced, and the time-consuming phase unwrapping in traditional phase shift methods is avoided. This algorithm is eventually implemented on DM3730 embedded system for 3-D measuring, which consists of an ARM and a DSP core and has a strong capability of digital signal processing. Experimental results demonstrated the feasibility of the proposed method.

Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.

We propose using the Abbe transform to design binary computer-generated hologram (CGH). We consider the edges of the apertures as the basic diffraction elements and the diffraction pattern of the entire CGH as a coherent summation of all the light diffracted from all the edges. The Abbe transform computes the diffraction of polygonal apertures by the analytical formula with computation time independent of the size of the apertures. We globally optimized the apertures in the CGH using the Genetic Algorithm with local search, followed by an optimization of floating co-vertices of the elementary apertures and obtained high performance CGHs.

Direct search with random trajectory (DSRT) method applied to the task of minimization of kinoform synthesis error is similar to direct binary search method for binary holograms synthesis. Main difference is that used method is designed to process arrays with multiple phase levels. First, kinoform is generated with conventional method such as Gerchberg-Saxton. Then, elements of kinoform are sequentially switched to obtain lower synthesis error value. This process goes on until minimum error value is reached. Analysis of performance of the DSRT method depending on kinoform size and number of phase levels is conducted. Results of numerical experiments are presented.

With the development of optical technology, optical instruments become smaller and more integrated. Because of the high diffraction efficiency and light weight, binary optical elements become more and more popular. Binary optical elements can only blaze at one wavelength, it has high diffraction efficiency at design wavelength. But the diffraction efficiency of binary optical elements will decrease quickly with the change of wavelength. And this situation will have a big impact on image quality. Since double-layer BOE can blaze at two wavelengths, it has high diffraction efficiency at wide spectral bandwidth. There are kinds of fabrication errors. Based on scalar diffraction theory, this paper analyzes the diffraction efficiency of double-layer BOE with fabrication errors and simulates it in MATLAB. Simulation shows the diffraction efficiency decreases quickly if the depth errors of two layers are opposite, and this situation should be avoided. As for periodic errors, tilt errors and angular errors, these fabrication errors have different impact of double-layer BOE on diffraction efficiency.

We introduce a multiscale image fusion scheme based on guided filtering. Guided filtering can effectively reduce noise while preserving detail boundaries. When applied in an iterative mode, guided filtering selectively eliminates small scale details while restoring larger scale edges. The proposed multi-scale image fusion scheme achieves optimal spatial consistency by using guided filtering both at the decomposition and at the recombination stage of the multiscale fusion process. First, size-selective iterative guided filtering is applied to decompose the source images into base and detail layers at multiple levels of resolution. Then, frequency-tuned filtering is used to compute saliency maps at successive levels of resolution. Next, at each resolution level a binary weighting map is obtained as the pixelwise maximum of corresponding source saliency maps. Guided filtering of the binary weighting maps with their corresponding source images as guidance images serves to reduce noise and to restore spatial consistency. The final fused image is obtained as the weighted recombination of the individual detail layers and the mean of the lowest resolution base layers. Application of multiband visual (intensified) and thermal infrared imagery demonstrates that the proposed method obtains state-ofthe-art performance for the fusion of multispectral nightvision images. The method has a simple implementation and is computationally efficient.

Laser image data-based target recognition technology is one of the key technologies of laser active imaging systems. This paper discussed the status quo of 3-D imaging development at home and abroad, analyzed the current technological bottlenecks, and built a prototype of range-gated systems to obtain a set of range-gated slice images, and then constructed the 3-D images of the target by binary method and centroid method, respectively, and by constructing different numbers of slice images explored the relationship between the number of images and the reconstruction accuracy in the 3-D image reconstruction process. The experiment analyzed the impact of two algorithms, binary method and centroid method, on the results of 3-D image reconstruction. In the binary method, a comparative analysis was made on the impact of different threshold values on the results of reconstruction, where 0.1, 0.2, 0.3 and adaptive threshold values were selected for 3-D reconstruction of the slice images. In the centroid method, 15, 10, 6, 3, and 2 images were respectively used to realize 3-D reconstruction. Experimental results showed that with the same number of slice images, the accuracy of centroid method was higher than the binary algorithm, and the binary algorithm had a large dependence on the selection of threshold; with the number of slice images dwindling, the accuracy of images reconstructed by centroid method continued to reduce, and at least three slice images were required in order to obtain one 3-D image.

International audience; The track-before-detect (TBD) approach can be used to track a single target in a highly noisy radar scene. This is because it makes use of unthresholded observations and incorporates a binary target existence variable into its target state estimation process when implemented as a particle filter (PF). This paper proposes the recursive PF-TBD approach to detect multiple targets in low-signal-to noise ratios (SNR). The algorithm’s successful performance is demonstrated using a simulated two target example.

To catalog space objects, the position and angular rate of the detected object must be determined; however, the quality of this data is restricted by the capability to determine the telescope’s pointing azimuth and elevation. The commonly used Binary Hypothesis Test (BHT) determines whether an object is present in an image or not by calculating the ratio of the probability of whether an object is present in each pixel to the probability of an object not being present. If this ratio exceeds a specified threshold, an object has been detected. The Multiple Hypothesis Test (MHT) operates similarly to the BHT but includes the additional step of correlating the image data against sampled Point Spread Functions (PSF). These PSFs appear differently based on the sub-pixel location of the object. The PSF with the strongest correlation to the image data indicates that the detected object is likely in the same sub-pixel location. Using the MHT can improve the ability to determine the telescope’s azimuth and elevation by observing objects at known locations. The data will be gathered through projecting a star map and using a telescope to locate the objects. This experimental data will provide verification and quantification of the improved accuracy of using the multi-hypothesis test.

This paper proposes a novel video stabilization method based on FREAK. That method combines the advantages of the fast speed of binary features and the high efficiency and robustness to parallax of 2D feature trajectories, which avoids inheriting the limitation to parallax from other 2D methods. In order to make the smoothed camera paths as flat as shot by a smoothly moving platform, we take full consideration of 2-degree gradients of the trajectories. This is done by adding a 2-degree regularization to the bundled paths optimization equations. Moreover, a spectral technique is employed to improve the accuracy of original feature matching results. Experiments demonstrate the competitive performance of our proposed method.

Cascade shape regression has been proven to be an accurate, robust and fast framework for face alignment. Recently, a lot of methods based on this framework have emerged which focus on boosting learning method or extracting geometric invariant features. Despite the great success of these methods, none of them are initialization independent, which limits their prediction performance to some complex face shapes. In this paper, we propose a novel initialization scheme called high-quality initial shape estimation to generate high-quality initial face shapes. First, we extract Gabor features to represent facial appearance. Then we minimize the square error between the target shapes and the estimated initial shapes using a random regression forest and binary comparison features. Finally, we use a standard cascade shape regressor to regress the estimated initial shape for robust face alignment. Experimental results show that our method achieves state-of-the-art performance on the 300-W dataset, which is the most challenging dataset today.

Through in-depth study of the existing discrete cosine transform (DCT) watermarking technology, this paper presents a double encryption watermarking algorithm to enhance the security of watermark information. In the watermark embedding stage presents a new adaptive blind watermarking algorithm based on DCT domain, to achieve binary watermark embedding after double encryption. This algorithm effectively reduces the complexity of the watermark extraction algorithm, and ensures the security of watermark while improving the invisibility, so it has a strong confidentiality, robustness and resistance to attack.

Credit card account number detection and extraction from camera-based images is of vital importance in automatically inputting system of mobile devices. In this paper, we propose a novel framework to detect and extract credit card account number from camera-based images. Firstly radon transformation is used to detect and correct the degree of skew of the credit card, Secondly a morphological binary map is generated by calculating difference between the closing image and the opening image. Then horizontal projection and k-means are applied to get the card-number lines. Candidate regions are connected by using a morphological dilation operation. Last text lines are refined using a sliding window and an SVM classifier trained on two local texture distribution features: HOG and an improved local region binary pattern (LRBP). Experiences show the proposed method is robust to different contrast and complex environment.

The mercury-manganese (HgMn) stars are a class of peculiar main-sequence late-type B stars. Their members show a wide variety of abundance anomalies with both depletions (e.g., He) and enhancements (Hg, Mn) and tend to be slow rotators relative to their normal analogs. More than two thirds of the HgMn stars are known to belong to spectroscopic binaries with a preference of orbital periods ranging from 3 to 20 days. 1 Interferometric orbits were already measured for the HgMn binaries Φ Herculis, 2 X Lupi, 3 and α Andromedae. 4 Here we report on a program to study the binarity of HgMn stars with the PIONIER near-infrared interferometer at the VLTI on Cerro Paranal, Chile. Among 40 stars, companions were found for 11 of them, and the data allowed the determination of the orbital elements of 41 Eridani, with a period of just 5 days and a semi-major axis of under 2 mas.

Some carbon-rich Wolf-Rayet stars are permanent dust producers, as seen by their infrared excess. In famous targets like WR104, the dust is found in the form of a pinwheel nebula around the central source, providing an indirect evidence of binarity. WR104 has been studied in details with the Keck, and more recently with the VLTI by our team. We present here images obtained with the SPHERE instrument and modelling based on AMBER data. First results show that the pinwheel appears to be diluted by diffuse emission. Moreover, a minimum distance between the central binary and the dust-formation zone appears necessary to reproduce both the AMBER and SPHERE data.

As sky surveys continue to document an increasing number of transient celestial phenomena, an intriguing subset of objects are emerging that show variations in brightness, interpreted as the transit of a circumstellar disk in front of a companion star in a binary system. The brightest member of this class is the F0 supergiant star plus disk binary, epsilon Aurigae, along with more than a dozen new candidates sharing similarities. Better-known cases include EE Cep, BM Ori and KH15D. Characteristics of all of these are discussed in terms of their suitability for interferometric study. Next generation interferometric imaging offers the potential to detect disk structures that are driven by dynamical forces, chemical transitions and thermal gradients. These include observable effects of tidal spiral density waves, dust and planetessimal formation/evolution in disks, and orbital phase-dependent heating of the disk by the external companion star.

IRBis is an image reconstruction method for optical/infrared long-baseline interferometry. IRBis can reconstruct images from (a) measured visibilities and closure phases, or from (b) measured complex visibilities (i.e. the Fourier phases and visibilities). The applied optimization routine ASA CG is based on conjugate gradients. The method allows the user to implement different regularizers, as for example, maximum entropy, smoothness, total variation, etc., and apply residual ratios as an additional metric for goodness-of-fit. In addition, IRBis allows the user to change the following reconstruction parameters: (a) FOV of the area to be reconstructed, (b) the size of the pixel-grid used, (c) size of a binary mask in image space allowing reconstructed intensities < 0 within the binary mask only, (d) the strength of the regularization, etc. The two main reconstruction parameters are the size of the binary mask in image space (c) and the strength of the regularization (d). Several values of these two parameters are tested within the algorithm. The quality of the different reconstructions obtained is roughly estimated by evaluation of the differences between the measured data and the reconstructed image (using the reduced χ2 values and the residual ratios). The best-quality reconstruction and a few reconstructions sorted according to their quality are provided to the user as resulting reconstructions. We describe the theory of IRBis and will present several applications to simulated interferometric data and data of real astronomical objects: (a) We have investigated image reconstruction experiments of MATISSE target candidates by computer simulations. We have modeled gaps in a disk of a young stellar object and have simulated interferometric data (squared visibilities and closure phases) with a signal-to-noise ratio as expected for MATISSE observations. We have performed image reconstruction experiments with this model for different flux levels of the target and different amount of observing time, that is, with different uv coverages. As expected, the quality of the reconstructions clearly depends on the flux of the source and the completeness of the uv coverage. (b) We also discuss reconstructions of the Luminous Blue Variable η Carinae obtained from AMBER observations in the high spectral resolution mode in the K band. The images were reconstruction (1) using the closure phases and (2) using the absolute phases derived from the measured wavelength-differential phases and the closure phase reconstruction in the continuum.

One of the 3D display systems for full-color reconstruction by using binary phase modulation is presented. The improvement of reconstructed objects is achieved by optimizing the binary phase modulation and accumulating the speckle patterns by changing the random phase distributions. The binary phase pattern is optimized by the modified Frenel ping-pong algorithm. Numerical and experimental demonstrations of full color reconstruction are presented.

In this paper, Single-Target-Oriented (STO) Binary Sensor Sets (BSSs) are introduced and analyzed for C3I applications. These STO BSSs are diversified multisensors (combining IR camera, LIDAR, radar, etc.) standardized into the Binary Sensor format. By increasing the k-number of Binary Sensors within the STO paradigm, we can increase target detection predictability, thus, increasing Bayesian inference strength.

A typical infrared (IR) thermographic system intended for active thermal/IR nondestructive testing includes a heat source, an IR imager and a computer. The software ensures acquisition and processing of IR image sequences to result in a binary map of defects or other image which is to be interpreted by a thermographer in order to meet inspection requirements. Typically, hardware developers supply a certain set of technical parameters of their units, such as heater power, imager temperature resolution, acquisition rate and a set of available data processing algorithms. The suggested approach allows optimization of inspection parameters if thermal and optical parameters of test materials are known.

The QIS was conceived when contemplating shrinking pixel sizes and storage capacities, and the steady increase in digital processing power. In the single-bit QIS, the output of each field is a binary bit plane, where each bit represents the presence or absence of at least one photoelectron in a photodetector. A series of bit planes is generated through high-speed readout, and a kernel or “cubicle” of bits (x,y,t) is used to create a single output image pixel. The size of the cubicle can be adjusted post-acquisition to optimize image quality. The specialized sub-diffraction-limit photodetectors in the QIS are referred to as “jots” and a QIS may have a gigajot or more, read out at 1000 fps, for a data rate exceeding 1Tb/s. Basically, we are trying to count photons as they arrive at the sensor. This paper reviews the Quanta Image Sensor (QIS) concept and its imaging characteristics. Recent progress towards realizing the QIS for commercial and scientific purposes is discussed. The QIS represents a possible major paradigm shift in image capture.

Automatic targets recognition(ATR) of artificial objects in high resolution remote sensing images can be divided into two categories by the properties of targets. The first such building, a harbor which has fixed location and stable out looking. The other one, for example aircraft, whose location and posture is sensitive to the moment. Due to the variable sizes, colors, orientations, and complex background, aircraft detection is a difficult task in high resolution remote sensing images. In this paper, a simple and effective aircraft detection method with a single template is proposed, which exactly locates the object by outputting its geometric center, location and orientation. Compare to traditional method,this method only needs critical feature in the local areas of target and a binary template of aircraft. Compare to traditional Feature + Classifier method, it’s easy, simple and don’t need outline training,but also get high precision and low false rate in the same complicate background.

The serious information redundancy in hyperspectral images (HIs) cannot contribute to the data analysis accuracy, instead it require expensive computational resources. Consequently, to identify the most useful and valuable information from the HIs, thereby improve the accuracy of data analysis, this paper proposed a novel hyperspectral band selection method using the hybrid genetic algorithm and gravitational search algorithm (GA-GSA). In the proposed method, the GA-GSA is mapped to the binary space at first. Then, the accuracy of the support vector machine (SVM) classifier and the number of selected spectral bands are utilized to measure the discriminative capability of the band subset. Finally, the band subset with the smallest number of spectral bands as well as covers the most useful and valuable information is obtained. To verify the effectiveness of the proposed method, studies conducted on an AVIRIS image against two recently proposed state-of-the-art GSA variants are presented. The experimental results revealed the superiority of the proposed method and indicated that the method can indeed considerably reduce data storage costs and efficiently identify the band subset with stable and high classification precision.

In this paper we compare the coding efficiency of AVS 2.0[1] for engines of the Context-based Binary Arithmetic Coding (CBAC) [2] in the AVS 2.0 and the Context-Adaptive Binary Arithmetic Coder (CABAC) [3] in the HEVC [4] . For fair comparison, the CABAC is embedded in the reference code RD10.1 because the CBAC is in the HEVC in our previous work [5] . The rate estimation table is employed only for RDOQ in the RD code. To reduce the computation complexity of the video encoder, therefore we modified the RD code so that the rate estimation table is employed for all RDO decision. Furthermore, we also simplify the complexity of rate estimation table by reducing the bit depth of its fractional part to 2 from 8. The simulation result shows that the CABAC has the BD-rate loss of about 0.7% compared to the CBAC. It seems that the CBAC is a little more efficient than that the CABAC in the AVS 2.0.

The possibility of formation of the beam with edge dislocation, which is similar to the ТЕ01(10) beam is considered. It is shown that such mode may be obtained due to the diffraction of Gaussian beam on the special binary computer generated hologram. The conditions of such operation are formulated. The experimental results and results of computer simulation are presented.

Image information onboard processing is one o f important technology to rapidly achieve intelligence for remote sensing satellites. As a typical target, aircraft onboard detection has been getting more attention. In this paper, we propose an efficient method of aircraft detection for remote sensing satellite onboard processing. According to the feature of aircraft performance in remote sensing image, the detection algorithm consists of two steps: First Salient Object Detection (SOD) is employed to reduce the amount of calculation on large remote sensing image. SOD uses Gabor filtering and a simple binary test between pixels in a filtered image. White points are connected as regions. Plane candidate regions are screened from white regions by area, length and width of connected region. Next a new algorithm, called Circumferential Information Matching method, is used to detect aircraft on candidate regions. The results of tests show circumference curve around the plane center is stable shape, so the candidate region can be accurately detecting with this feature. In order to rotation invariant, we use circle matched filter to detect target. And discrete fast Fourier transform (DFFT) is used to accelerate and reduce calculation. Experiments show the detection accuracy rate of proposed algorithm is 90% with less than 0.5s processing time. In addition, the calculation of the proposed method through quantitative anglicized is very small. Experimental results and theoretical analysis show that the proposed method is reasonable and highly-efficient.

Fringe projection profilometry (FPP) is a rapidly developing technique which is widely used for industrial manufacture, heritage conservation, and medicine etc. because of its high speed, high precision, non-contact operation, full-field acquisition, and easy information processing. Among the various FFP methods, the squared binary defocused projection method (SBM) has been promptly expanding with several advantages: (1) high projection speed because of 1-bit grayscale fringe; (2) eliminating nonlinear gamma of the projector for the defocusing effect. Nevertheless, the method is not trouble-free. When the fringe stripe is wide, it brings down the fringe contrast and is difficult to control the defocused degree, resulting in a low measurement accuracy. In order to further improve high-speed and high-precision three-dimensional shape measurement, this paper presents a new three-dimensional shape measurement method based on double-frequency fringes projection. This new method needs to project two sets of 1-bit grayscale fringe patterns (low-frequency fringe and high-frequency fringe) onto the object surface under slightly defocused projection mode. The method has the following advantages: (1) high projection speed because of 1-bit grayscale fringe; (2) high measurement precision for selectively removing undesired harmonics. Low-frequency fringe is produced by error-diffusion dithering (Dithering) technique and high-frequency fringe is generated by optimal pulse-width modulation (OPWM) technique. The two kinds of fringe patterns have each superiorities and flaws. The low-frequency fringe has a low measurement accuracy, but the continue phase can be easily retrieved. However, the property of high-frequency fringe and low-frequency fringe is the opposite. The general idea of this method proposed is as follows: Because the both fringes test the same object, the height is the same. The low-frequency fringe can be used to assist the high frequency fringe to retrieve continue phase map, then the three-dimensional shape information of the object can be obtained. Theory analyzes the mathematical principle of error-diffusion dithering technique, optimal pulse-width modulation technique and three-dimensional reconstructed algorithm based on double-frequency fringes projection. A second-hand mouse was used to test the proposed method. The experiment results show that the three-dimensional shape measurement method combining OPWM technique and Dithering technique can achieve fast-speed and high-precision three-dimensional shape measurement.

Recording of binary volumetric diffractive optical elements within a 13 μm thick photosensitive chalcogenide layer using an innovative exposure set-up based on digital micro-mirrors devices is demonstrated. Different examples of beam transformations are shown such as the conversion of Gaussian beam into higher order modes or top-hat beam shapers.

Distributed occulter/telescope systems hold great promise in the field of direct exoplanet imaging. However, proposed missions using this concept such as the New Worlds Observer or Exo-S (NASA) are exceptionally large with occulter diameters of tens of meters and inter-spacecraft separations of tens of megameters, requiring deployment in deep space. The estimated costs associated with these missions are in the billions of dollars. In order to reduce the risk associated with these missions, it is desirable to first deploy a low-cost technology demonstrator mission to prove that the distributed occulter telescope concept is valid. To that end, this work assesses the feasibility of miniaturizing the optics of the distributed occulter/telescope to enable deployment on micro- or nano-satellites in earth orbit. A variant of the convex optimization formulation introduced by previous authors is used to generate a pareto-optimal characterization between the achievable occulter contrast and a set of critical design variables (occulter radius, inner working angle, science spectrum, etc). This characterization is performed for two different sets of engineering constraints, corresponding to different levels of design complexity. The results of this study are compared to the performance requirements for imaging targets of scientific interest, namely exozodiacal dust disks, in order to identify promising design envelopes. The result of this work is a comprehensive trade of the capabilities of miniaturized, binary, petal-shaped occulters. This research demonstrates that there exist miniaturized occulter geometries compatible with micro- or nano-satellites in earth orbit suitable for imaging exozodiacal dust disks. In addition, this study provides a valuable methodology and performance guidelines for future distributed occulter/telescope designs.

Image-based modeling and rendering is currently one of the most challenging topics in Computer Vision and Photogrammetry. The key issue here is building a set of dense correspondence points between two images, namely dense matching or stereo matching. Among all dense matching algorithms, Semi-Global Matching (SGM) is arguably one of the most promising algorithms for real-time stereo vision. Compared with global matching algorithms, SGM aggregates matching cost from several (eight or sixteen) directions rather than only the epipolar line using Dynamic Programming (DP). Thus, SGM eliminates the classical “streaking problem” and greatly improves its accuracy and efficiency. In this paper, we aim at further improvement of SGM accuracy without increasing the computational cost. We propose setting the penalty parameters adaptively according to image edges extracted by edge detectors. We have carried out experiments on the standard Middlebury stereo dataset and evaluated the performance of our modified method with the ground truth. The results have shown a noticeable accuracy improvement compared with the results using fixed penalty parameters while the runtime computational cost was not increased.

Imaging and measurement of diffusion process in liquid solutions is a challenging and interesting problem. Especially the mixing of binary liquid solutions in real-time provides an insight into the physics of diffusion as well as leads to measurement of diffusion coefficient, which is the most important parameter of a diffusing liquid solution. Accurate measurement of diffusion coefficient is important in areas ranging from oil extraction to pollution control. Interferometric methods provides very accurate measurement of diffusion coefficients albeit they impose very stringent optical conditions. Here we describe the development of a compact, easy to implement, easy to use and inexpensive device for imaging and quantification of the diffusion process. This technique does not require the stringent optical conditions of interferometric techniques. It computes the diffusivity values by measuring the amount of deflection happening to a line pattern printed on a paper and projected through the sample cell. The measured diffusivity values varied by less than 1%, with the values of diffusivities reported in literature.

In the framework of ERMES project (FP7 66983), an algorithm for mapping rice cultivation extents using mediumhigh resolution satellite data was developed. ERMES (An Earth obseRvation Model based RicE information Service) aims to develop a prototype of downstream service for rice yield modelling based on a combination of Earth Observation and in situ data. The algorithm was designed as a set of rules applied on a time series of Landsat 8 images, acquired throughout the rice cultivation season of 2014 from the plain of Thessaloniki, Greece. The rules rely on the use of spectral indices, such as the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), and the Normalized Seasonal Wetness Index (NSWI), extracted from the Landsat 8 dataset. The algorithm is subdivided into two phases: a) a hard classification phase, resulting in a binary map (rice/no-rice), where pixels are judged according to their performance in all the images of the time series, while index thresholds were defined after a trial and error approach; b) a soft classification phase, resulting in a fuzzy map, by assigning scores to the pixels which passed (as ‘rice’) the first phase. Finally, a user-defined threshold of the fuzzy score will discriminate rice from no-rice pixels in the output map. The algorithm was tested in a subset of Thessaloniki plain against a set of selected field data. The results indicated an overall accuracy of the algorithm higher than 97%. The algorithm was also applied in a study are in Spain (Valencia) and a preliminary test indicated a similar performance, i.e. about 98%. Currently, the algorithm is being modified, so as to map rice extents early in the cultivation season (by the end of June), with a view to contribute more substantially to the rice yield prediction service of ERMES. Both algorithm modes (late and early) are planned to be tested in extra Mediterranean study areas, in Greece, Italy, and Spain.

All-optical systems for binary to Gray code conversion and Gray code to binary conversion are proposed where the input and output binary digits are expressed as the presence (=1) or the absence (=0) of a light signal. The intensity based optical XOR logic operation is used here to develop the scheme.

Microsystems for autonomous limit monitoring can be used for triggering maintenance and thus help to reduce costs. We present a fully integrated passive microsystem for binary counting of off-limit conditions. The mechanical design and a mechanical characterization of the system fabricated using SOI (silicon-on-insulator) technology are shown. The binary counting mechanism is realized by utilizing mechanical coupling elements between bit elements. The mechanical energy needed for switching the first bit to the state "high" was found to be 0.1 μJ by moving the entrance 37 μm and applying a force of up to 8.2 mN. 0.36 μJ was determined for switching the bit back to the state "low" by applying a 69 μm distance and a force of up to 10.2 mN. The system needs input energy for counting only, not for storing the counter value. Expanding the design to up to ten bit elements would offer a passive microsensor able to detect 1023 off-limit conditions. A mechanical binary microcounter is presented that does not require electrical energy supply. It is suitable for counting any physical event that can be converted into an adequate force-travel-characteristic.