Efficient single-pixel imaging encrypted transmission based on 3D Arnold transformation

Single-pixel imaging(SPI)can transform 2D or 3D image data into 1D light signals,which offers promising prospects for image compression and transmission.However,during data communication these light signals in public channels will easily draw the attention of eavesdroppers.Here,we introduce an efficient encryption method for SPI data transmission that uses the 3D Arnold transformation to directly disrupt 1D single-pixel light signals and utilizes the elliptic curve encryption algorithm for key transmission.This encryption scheme immediately employs Hadamard patterns to illuminate the scene and then utilizes the 3D Arnold transformation to permutate the 1D light signal of single-pixel detection.Then the transformation parameters serve as the secret key,while the security of key exchange is guaranteed by an elliptic curve-based key exchange mechanism.Compared with existing encryption schemes,both computer simulations and optical experiments have been conducted to demonstrate that the proposed technique not only enhances the security of encryption but also eliminates the need for complicated pattern scrambling rules.Additionally,this approach solves the problem of secure key transmission,thus ensuring the security of information and the quality of the decrypted images.

Applications of Lodrigues Matrix in 3D Coordinate Transformation

Three transformation models （Bursa-Wolf, Molodensky, and WTUSM） are generally used between two data systems transformation. The linear models are used when the rotation angles are small; however, when the rotation angles get bigger, model errors will be produced. In this paper, we present a method with three main terms：① the traditional rotation angles θ,φ,ψ are substituted with a,b,c which are three respective values in the anti-symmetrical or Lodrigues matrix; ② directly and accurately calculating the formula of seven parameters in any value of rotation angles; and ③ a corresponding adjustment model is established. This method does not use the triangle function. Instead it uses addition, subtraction, multiplication and division, and the complexity of the equation is reduced, making the calculation easy and quick.

A complete solution of an improved universal 3D coordinate similarity transformation model

When linearizing three-dimensional(3 D)coordinate similarity transformation model with large rotations,we usually encounter the ill-posed normal matrix which may aggravate the instability of solutions.To alleviate the problem,a series of conversions are contributed to the 3 D coordinate similarity transformation model in this paper.We deduced a complete solution for the 3 D coordinate similarity transformation at any rotation with the nonlinear adjustment methodology,which involves the errors of the common and the non-common points.Furthermore,as the large condition number of the normal matrix resulted in an intractable form,we introduced the bary-centralization technique and a surrogate process for deterministic element of the normal matrix,and proved its benefit for alleviating the condition number.The experimental results show that our approach can obtain the smaller condition number to stabilize the convergence of the interested parameters.Especially,our approach can be implemented for considering the errors of the common and the non-common points,thus the accuracy of the transformed coordinates improves.

2D/3D Isometric Transformation Using Spring-Mass System

This paper presents a general method for 2D/3D transformation, which can be efficiently used in three dimensional computer aided garment design. The method utilizes a uniform triangular spring_mass based deformable model. 2D to 3D transformation and 3D to 2D transformation both can be implemented on the same model. A general and efficient collision detection method is also briefly discussed in this paper.

Estimating primaries by sparse inversion of the 3D Curvelet transform and the L1-norm constraint

In this paper, we built upon the estimating primaries by sparse inversion （EPSI） method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and Ll-norm regularization, and use alternating optimization to directly estimate the primary reflection coefficients and source wavelet. The 3D curvelet transform is used as a sparseness constraint when inverting the primary reflection coefficients, which results in avoiding the prediction subtraction process in the surface-related multiples elimination （SRME） method. The proposed method not only reduces the damage to the effective waves but also improves the elimination of multiples. It is also a wave equation- based method for elimination of surface multiple reflections, which effectively removes surface multiples under complex submarine conditions.

Attention Guided Multi Scale Feature Fusion Network for Automatic Prostate Segmentation

The precise and automatic segmentation of prostate magnetic resonance imaging(MRI)images is vital for assisting doctors in diagnosing prostate diseases.In recent years,many advanced methods have been applied to prostate segmentation,but due to the variability caused by prostate diseases,automatic segmentation of the prostate presents significant challenges.In this paper,we propose an attention-guided multi-scale feature fusion network(AGMSF-Net)to segment prostate MRI images.We propose an attention mechanism for extracting multi-scale features,and introduce a 3D transformer module to enhance global feature representation by adding it during the transition phase from encoder to decoder.In the decoder stage,a feature fusion module is proposed to obtain global context information.We evaluate our model on MRI images of the prostate acquired from a local hospital.The relative volume difference(RVD)and dice similarity coefficient(DSC)between the results of automatic prostate segmentation and ground truth were 1.21%and 93.68%,respectively.To quantitatively evaluate prostate volume on MRI,which is of significant clinical significance,we propose a unique AGMSF-Net.The essential performance evaluation and validation experiments have demonstrated the effectiveness of our method in automatic prostate segmentation.

Multi-focus image fusion based on block matching in 3D transform domain

Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of image.This paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.

An iterative algorithm of NWTLS-EC for three dimensional-datum transformation with large rotation angle

The Gauss-Markov （GM） model and the Errors-in-Variables （EIV） model are frequently used to perform 3D coordinate transformations in geodesy and engineering surveys. In these applications, because the observation errors in original coordinates system are also taken into account, the latter is more accurate and reasonable than the former. Although the Weighted Total Least Squares （WTLS） technique has been intro- duced into coordinate transformations as the measured points are heteroscedastic and correlated, the Variance- Covariance Matrix （VCM） of observations is restricted by a particular structure, namely, only the correlations of each points are taken into account. Because the 3D datum transformation with large rotation angle is a non- linear problem, the WTLS is no longer suitable in this ease. In this contribution, we suggested the nonlinear WTLS adjustments with equality constraints （NWTLS-EC） for 3D datum transformation with large rotation an- gle, which removed the particular structure restriction on the VCM. The Least Squares adjustment with Equality （LSE） constraints is employed to solve NWTLS-EC as the nonlinear model has been linearized, and an iterative algorithm is proposed with the LSE solution. A simulation study of 3D datum transformation with large rotation angle is given to insight into the feasibility of our algorithm at last.

SARC Model for Three-Dimensional Coordinate Transformation

In this paper, a transformation model named SARC(static-filter adjustment with restricted condition) is presented, which is more practical and more rigorous in theory and fitting any angle of rotation parameter. The transformation procedure is divided into 4 steps: ① the original and object coordinates can be regarded as observations with errors; ② rigorous formula is firstly deduced in order to compute the first approximation of the transformation parameters by use of four common points and the transformation equation is linearized; ③ calculate the most probable values and variances of the seven transformation parameters by SARC model; ④ to demonstrate validity of SARC , an example is given.

3D Reconstruction and Animation of Brain MRI Images Based on Matlab

The following algorithms are proposed and realized by MATLAB programming based on the brain MRI images:(1)The 3D surface of the brain is reconstructed using MC algorithm.(2)A rotate animation of the brain is created and displayed by 3D rotate transformation and animation functions of Matlab.Result shows that the algorithm can show the brain accurately and quickly,takes up less space in memory.

Possibilities of GPS Kinematic Measurements for Geological Survey in East Slovakia

This paper deals with transformation procedures for observed GPS data from the world geodetic system WGS84 into the national geodetic grid datum SUTCN （system of united trigonometric cadaster network） and Baa（the Baltic Sea after adjustment）.Transformation from WGS84 into SUTCN is performed most frequently by means of the 7element Helmert transformation with three identical points.Geodetic network was adjusted by two ways.

3-D Wavelet Transform for Very Low Bit-Rate Video Coding

A new improved Goh's 3 D wavelet transform(WT) coding scheme is presented in this paper. The new scheme has great advantages including a simple code structure, low computation cost and good performance in PSNR, compression ratios and visual quality of reconstructions, when compared to the other existing 3 D WT coding methods and the 2 D WT based coding methods. The new 3 D WT coding scheme is suitable for very low bit rate video coding.

Very Low Bit Rate Video Coding Using Motion Compensated 3 D Wavelet Transform

A new motion compensated 3 D wavelet transform (MC 3DWT) video coding scheme is presented in this paper. The new coding scheme has a good performance in average PSNR, compression ratio and visual quality of reconstructions compared with the existing 3 D wavelet transform (3DWT) coding methods and motion compensated 2 D wavelet transform (MC WT) coding method. The new MC 3DWT coding scheme is suitable for very low bit rate video coding.

Laser speckle contrast imaging based on uniting spatiotemporal Fourier transform

We propose a laser speckle contrast imaging method based on uniting spatiotemporal Fourier transform.First,the raw speckle images are entirely transformed to the spatiotemporal frequency domain with a three-dimensional(3D)fast Fourier transform.Second,the dynamic and static speckle components are extracted by applying 3D low-pass and high-pass filtering in the spatiotemporal frequency domain and inverse 3D Fourier transform.Third,we calculate the time-averaged modulation depth with the average of both components to map the two-dimensional blood flow distribution.The experiments demonstrate that the proposed method could effectively improve computational efficiency and imaging quality.

Compression Algorithm for Implicit 3D B-Spline Solids

Due to advantages in solid modeling with complex geometry and its ideal suitability for 3D printing,the implicit representation has been widely used in recent years.The demand for free-form shapes makes the implicit tensor-product B-spline representation attract more and more attention.However,it is an important challenge to deal with the storage and transmission requirements of enormous coefficient ten-sor.In this paper,we propose a new compression framework for coefficient tensors of implicit 3D tensor-product B-spline solids.The proposed compression algorithm consists of four steps,i.e.,preprocessing,block splitting,using a lifting-based 3D discrete wavelet transform,and coding with 3D set partitioning in hierarchical trees algorithm.Finally,we manage to lessen the criticism of the implicit tensor-product B-spline representation of surface for its redundancy store of 3D coefficient tensor.Experimental results show that the proposed compression framework not only achieves satisfactory reconstruction quality and considerable compression ratios,but also sup-ports progressive transmissions and random access by employing patch-wise coding strategy.

Detecting the filamentary structure of 3D point clouds:Proposal of a wavelet-based method

The analysis of the filamentary structure of the cosmo as well as that of the internal structure of the polar ice suggests the development of models based on three-dimensional(3D)point processes.A point process,regarded as a random measure,can be expressed as a sum of Delta Dirac measures concentrated at some random points.The integration with respect to the point process leads the continuous wavelet transform of the process itself.As possible mother wavelets,we propose the application of the Mexican hat and the Morlet wavelet in order to implement the scale-angle energy density of the process,depending on the dilation parameter and on the three angles which define the direction in the Euclidean space.Such indicator proves to be a sensitive detector of any variation in the direction and it can be successfully implemented to study the isotropy or the filamentary structure in 3D point patterns.

Generation and Application of Spatial Atmospheric Turbulence Field in Flight Simulation

This article deals with generation and application of three-dimensional (3D) atmospheric turbulence field in large aircraft real-time flight simulation. The modeling requirements for the turbulence field of large aircraft flight simulation are analyzed here. The spatial turbulence field is generated in the frequency domain by using the Monte Carlo method,and then transformed back to the time domain with the 3D inverse Fourier transform. The von Karman model is adopted for an accurate description of the turb...

Study of Human Action Recognition Based on Improved Spatio-temporal Features

Most of the exist action recognition methods mainly utilize spatio-temporal descriptors of single interest point while ignoring their potential integral information, such as spatial distribution information. By combining local spatio-temporal feature and global positional distribution information(PDI) of interest points, a novel motion descriptor is proposed in this paper. The proposed method detects interest points by using an improved interest point detection method. Then, 3-dimensional scale-invariant feature transform(3D SIFT) descriptors are extracted for every interest point. In order to obtain a compact description and efficient computation, the principal component analysis(PCA) method is utilized twice on the 3D SIFT descriptors of single frame and multiple frames. Simultaneously, the PDI of the interest points are computed and combined with the above features. The combined features are quantified and selected and finally tested by using the support vector machine(SVM) recognition algorithm on the public KTH dataset. The testing results have showed that the recognition rate has been significantly improved and the proposed features can more accurately describe human motion with high adaptability to scenarios.

A new three-dimensional elastography using phase based shifted Fourier transform

Elastography is an imaging technique with the ability to determine low quantities of some of the mechanical properties of tissues.The aim of our research is to design a new 3D algorithm using the Shifted Fourier Transform(SFT)to perform a quasi-static elastography.Our innovative idea is implementation of a 3D convolution instead of using three 2D convulsions.At first,we collected the raw data from Abaqus engineering software in the form of breast tissue with a coefficient of elasticity of healthy tissue and tumor tissue with a coefficient of elasticity of tumor tissue.The primary raw data consists of a number of points with x,y and z specified for tumor and healthy breast tissue.At this step,we simulated the displacements in directions of x,y and z at each point of the prescribed tissues for 15 mm displacement of probe in–Y direction then we collected 1831 points for tumor and 4186 points for breast before and after pressure.After applying a novel reconstruction algorithm,we convolved all images with the 3D Gabor filters to obtain phases,represented displacements of the breast and tumor images for before and after pressure.To reach this goal,we designed a Gabor filter bank based on the dimensions of the input images in different scales,directions,and deviations.Using the 3D SFT,we calculated the displacements of the breast and tumor tissues followed by 3D elastogram representation of the images.Finally,we implemented a 2D analysis of SFT in order to investigate validation of the 3D SFT.In 2D algorithm,we used three two-dimensional convulsions in XY,YZ and XZ planes.The results obtained from the small displacements marked by circles,confirmed the accuracy of the 3D SFT algorithm.These areas of interest are the tumor areas in the 2D analysis.