Integer multiple quantum image scaling based on NEQR and bicubic interpolation

As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.

Performance of global look-up table strategy in digital image correlation with cubic B-spline interpolation and bicubic interpolation

Global look-up table strategy proposed recently has been proven to be an efficient method to accelerate the interpolation, which is the most time-consuming part in the iterative sub-pixel digital image correlation （DIC） algorithms. In this paper, a global look-up table strategy with cubic B-spline interpolation is developed for the DIC method based on the inverse compositional Gauss-Newton （IC-GN） algorithm. The performance of this strategy, including accuracy, precision, and computation efficiency, is evaluated through a theoretical and experimental study, using the one with widely employed bicubic interpolation as a benchmark. The global look-up table strategy with cubic B-spline interpolation improves significantly the accuracy of the IC-GN algorithm-based DIC method compared with the one using the bicubic interpolation, at a trivial price of computation efficiency.

An improved bicubic imaging fitting algorithm for 3D radar detection target

3D ground-penetrating radar has been widely used in urban road underground disease detection due to its nondestructive,efficient,and intuitive results.However,the 3D imaging of the underground target body presents the edge plate phenomenon due to the space between the 3D radar array antennas.Consequently,direct 3D imaging using detection results cannot reflect underground spatial distribution characteristics.Due to the wide-beam polarization of the ground-penetrating radar antenna,the emission of electromagnetic waves with a specific width decreases the strong middle energy on both sides gradually.Therefore,a bicubic high-precision 3D target body slice-imaging fitting algorithm with changing trend characteristics is constructed by combining the subsurface target characteristics with the changing spatial morphology trends.Using the wide-angle polarization antenna’s characteristics in the algorithm to build the trend factor between the measurement lines,the target body change trend and the edge detail portrayal achieve a 3D ground-penetrating radar-detection target high-precision fitting.Compared with other traditional fitting techniques,the fitting error is small.This paper conducts experiments and analyses on GpaMax 3D forward modeling and 3D ground-penetrating measured radar data.The experiments show that the improved bicubic fitting algorithm can eff ectively improve the accuracy of underground target slice imaging and the 3D ground-penetrating radar’s anomaly interpretation.

Modeling the Dynamic Gravity Variations of Northeastern Margin of Qinghai-Xizang (Tibet) Plateau by Using Bicubic Spline Interpolation Function

In this paper, the spatial-temporal gravity variation patterns of the northeastern margin of Qinghal-Xizang （Tibet） Plateau in 1992 - 2001 are modeled using bicubic spline interpolation functions and the relations of gravity change with seismicity and tectonic movement are discussed preliminarily. The results show as follows： ① Regional gravitational field changes regularly and the gravity abnormity zone or gravity concentration zone appears in the earthquake preparation process; ②In the significant time period, the gravity variation shows different features in the northwest, southeast and northeast parts of the surveyed region respectively, with Lanzhou as its boundary;③The gravity variation distribution is basically identical to the strike of tectonic fault zone of the region, and the contour of gravity variation is closely related to the fault distribution.

Fairing of Parametric Cubic B-spline Curves and Bicubic B-spline Surfaces

A method of fairing parametric cubic B_spline curves and bicubic B_spline surfaces is presented. The basic idea of the method is to reposition the control points by an optimization process.A new objectijve function presented is based on the variation of the third order derivatives of the cubic B_spline curves and bicubic B_spline surfaces at the nodes. The curves and surfaces faired using this method tend to possess curvature continuities. The numerical examples show that the effect of this method is acceptable.

Contour detection with bicubic spline surfaces

Contour detection has a rich history in multiplefields such as geography,engineering,and earth science.The predominant approach is based on piecewise planar tessellation and now being challenged concerning the extraction of contour objects for non-linear elevation functions,particularly with respect to bicubic spline functions.A storage-efficient method was developed in previous research,but the detection of the complete set of contour objects is yet to be realized.Although intractable,theoretical underpinnings pertinent to curvature resulted in an approach to realize the complete detection of objects.Given a digital elevation model dataset,in this study,a bicubic spline surface function wasfirst determined.Thereafter,candidate initial points on the edges across the region of interest were identified,and the recursive disaggregation of rectangles was repeated if the non-existence of a solution could not be assured.A developed tracking method was then applied.During advancement,other initial points on the same contour curve were identified and eliminated to circumvent duplicate detection.The completeness of the outlets provides analytical tools for elevation and other geographical assessments.Demonstrative experiments included the development of a three-dimensional contour-based network and slope assessments.The latter application transforms the slope analysis type from raster-based to vector-based.Highlights.Detection of a complete set of contour objects amenable to bicubic spline surfaces..Small closure inside a single patch is detectable if size exceeds the standard..Curvature&tolerances central to step length adjustment and tangent angle determination..Redundant initial points are identified and eliminated during the tracking process..Various potential applications in addition to geographical elevations.

CONVERGENCE AND SUPERCONVERGENCE OF HERMITE BICUBIC ELEMENT FOR EIGENVALUE PROBLEM OF THE BIHARMONIC EQUATION

Provides information on a study which discussed the convergence and superconvergence for eigenvalue problem of the biharmonic equation using the Hermite bicubic element. Discussion on eigenvalue problem for biharmonic equation; Background on asymptotic error expansions and interpolation postprocessing; Superconvergence approximations to the eigenvalue and eigenfunction.

ANALYSIS OF BENDING, VIBRATION AND STABILITY FOR THIN PLATE ON ELASTIC FOUNDATION BY THE MULTIVARIABLE SPLINE ELEMENT METHOD

In this paper, the bicubic splines in product form are used to construct the multi-field functions for bending moments, twisting moment and transverse displacement of the plate on elastic foundation. The multivariable spline element equations are derived, based on the mixed variational principle. The analysis and calculations of bending, vibration and stability of the plates on elastic foundation are presented in the paper. Because the field functions of plate on elastic foundation are assumed independently, the precision of the field variables of bending moments and displacement is high.

Deformation Model Inferred from Focal Mechanisms in the Chinese Mainland and Its Adjacent Areas

We collect seismic moment tensors of the earthquakes occurring from 1900 to 2013 in and around the Chinese mainland and summarize the surface ruptures and displacements of 70 earthquakes with M S≥7. 0. We divide these large earthquakes into three types. Type A contains earthquakes with surface ruptures and displacements. Type B is earthquakes without displacements and Type C is those without any of this data. We simulate a triangular distribution of displacements for Type B and C. Then,we segment these large earthquakes by using their displacements and surface ruptures. Finally,kinematic models are determined from earthquake data and Bicubic Bessel spline functions. The results show that,first of all,the reasonability and spatial consistency of defined models are advanced.Strain rates have better continuity and are comparable with geologic and geodetic results in Himalaya thrust fault zones. The strain rates decrease in the Tarim basin and the Altun Tagh fault zones because of their low seismicity. The direction of compressional deformation in Gobi-Altay is changed from SE to NE and its extensional direction is changed from NE to NW. The extensional deformation in the Ordos block is diminished obviously. Secondly,earthquakes account for 30- 50% of expected motion of India relative to Eurasia determined from the NUVEL-1A model,with a missing component of 20 mm / a which may contain aseismic deformation such as fault creep and folds,the missing parts of earthquake data and elastic strain energy released by potential earthquakes.

Image Resolution Enhancement Using Spatially Invariant Point Spread Function

This paper presents an image resolution enhancement algorithm using spatially invariant point spread function.Point spread function is used to constrain the solution space.This parameter is computed at each iteration step using partially restored image at each iteration,and High pass filter is used to impose the degree of edge smoothness on the solution.The resulting iterative algorithm exhibits the increased PSNR better than Bicubic interpolation approach.

Effect of the Pixel Interpolation Method for Downsampling Medical Images on Deep Learning Accuracy

Background: High-resolution medical images often need to be downsampled because of the memory limitations of the hardware used for machine learning. Although various image interpolation methods are applicable to downsampling, the effect of data preprocessing on the learning performance of convolutional neural networks (CNNs) has not been fully investigated. Methods: In this study, five different pixel interpolation algorithms (nearest neighbor, bilinear, Hamming window, bicubic, and Lanczos interpolation) were used for image downsampling to investigate their effects on the prediction accuracy of a CNN. Chest X-ray images from the NIH public dataset were examined by downsampling 10 patterns. Results: The accuracy improved with a decreasing image size, and the best accuracy was achieved at 64 × 64 pixels. Among the interpolation methods, bicubic interpolation obtained the highest accuracy, followed by the Hamming window.

A Parameter Adaptive Method for Image Smoothing

Edge is the key information in the process of image smoothing. Some edges, especially the weak edges, are difficult to maintain, which result in the local area being over-smoothed. For the protection of weak edges, we propose an image smoothing algorithm based on global sparse structure and parameter adaptation. The algorithm decomposes the image into high frequency and low frequency part based on global sparse structure. The low frequency part contains less texture information which is relatively easy to smoothen. The high frequency part is more sensitive to edge information so it is more suitable for the selection of smoothing parameters. To reduce the computational complexity and improve the effect, we propose a bicubic polynomial fitting method to fit all the sample values into a surface. Finally, we use Alternating Direction Method of Multipliers (ADMM) to unify the whole algorithm and obtain the smoothed results by iterative optimization. Compared with traditional methods and deep learning methods, as well as the application tasks of edge extraction, image abstraction, pseudo-boundary removal, and image enhancement, it shows that our algorithm can preserve the local weak edge of the image more effectively, and the visual effect of smoothed results is better.