Two-level Bregmanized method for image interpolation with graph regularized sparse coding

A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.

Approach for ISAR imaging of near-field targets based on coordinate conversion and image interpolation

Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.In this paper,the simplified target model with uniform linear motion is applied to the near-field target imaging,which overcomes the complexity of the traditional near-field imaging algorithm.According to this signal model,the method based on coordinate conversion and image interpolation combined with the range-Doppler(R-D)algorithm is proposed to correct the near-field distortion problem.Compared with the back-projection(BP)algorithm,the proposed method produces better focused ISAR images of the near-field target,and decreases the computation complexity significantly.Experimental results of the simulated data have demonstrated the effectiveness and robustness of the proposed method.

FEATURE PRESERVING IMAGE INTERPOLATION BY ADAPTIVE BIDIRECTIONAL FLOW

Most image interpolation algorithms currently used suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This letter presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the iso-phote lines (edges), while a normal diffusion is done to remove artifacts ('jaggies') along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first order and the second order directional derivatives of the image. Experimental results on the Lena image demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.

Image Interpolation via Gaussian-Sinc Interpolators with Partition of Unity

In this paper,we propose a novel image interpolation method by using Gaussian-Sinc automatic interpolators with partition of unity property.A comprehensive comparison is made with classical image interpolation methods,such as the bicubic interpolation,Lanczos interpolation,cubic Schaum interpolation,cubic B-spline interpolation and cubic Moms interpolation.The experimental results show the effectiveness of the improved image interpolation method via some image quality metrics such as PSNR and SSIM.

A psychophysical-based fuzzy image interpolation algorithm

To produce a smoother and more natural interpolated image, and to preserve and enhance original image details, we defined three perception-based local statistic parameters, namely contrast, noise visibility, and edge strength based on three psychophysical principles, including Weber’s Law, Fechner’s Law, and Stevens’ Power Law, and integrated these parameters into a fuzzy logic system to set up an advanced image interpolation algorithm. Application of this algorithm to detect edge behaviors and local statistical information of images demonstrated better noise removal ability and obtained sharper edges than traditional image interpolation algorithems such as nearest neighbor, bilinear and bicubic interpolation methods.

3D Medical Image Interpolation Based on Parametric Cubic Convolution

In the process of display, manipulation and analysis of biomedical image data, they usually need to be converted to data of isotropic discretization through the process of interpolation, while the cubic convolution interpolation is widely used due to its good tradeoff between computational cost and accuracy. In this paper, we present a whole concept for the 3D medical image interpolation based on cubic convolution, and the six methods, with the different sharp control parameter,which are formulated in details. Furthermore, we also give an objective comparison for these methods using data sets with the different slice spacing. Each slice in these data sets is estimated by each interpolation method and compared with the original slice using three measures: mean-squared difference, number of sites of disagreement, and largest difference. According to the experimental results, we present a recommendation for 3D medical images under the different situations in the end.

Two-direction nonlocal model for image interpolation

How to sufficiently exploit the self-similarity of natural images for image restoration has attracted extensive interest in the field of image processing in recent years.In fact,the self-similarity implies two-direction similarity structures inherent in images,when a group of similar patches are rearranged to form a matrix,there exists similarity between both columns and rows of this matrix.In this paper,we propose a two-direction nonlocal model (TDNL) to symmetrically exploit the two-direction similarity structures in images,the model directly takes the similar patches as local adaptive dictionary to represent each patch in the image and constrain the representation coefficients by Tikhonov regularization.TDNL can achieve the best results so far and obtain significant gains over the existing methods,in terms of both peak signal to noise ratio (PSNR) measure and the visual quality when it is applied to the problem of image interpolation.

Homography-guided stereo matching for wide-baseline image interpolation

Image interpolation has a wide range of applications such as frame rate-up conversion and free viewpoint TV.Despite significant progresses,it remains an open challenge especially for image pairs with large displacements.In this paper,we first propose a novel optimization algorithm for motion estimation,which combines the advantages of both global optimization and a local parametric transformation model.We perform optimization over dynamic label sets,which are modified after each iteration using the prior of piecewise consistency to avoid local minima.Then we apply it to an image interpolation framework including occlusion handling and intermediate image interpolation.We validate the performance of our algorithm experimentally,and show that our approach achieves state-of-the-art performance.

Rapid ultrasonic C-scan on image test for spot welding based interpolation

In this paper, ultrasonic C-scan test of spot welds for stainless steel has been studied. It is concluded that large scanning step length contributes to high testing efficiency, however, the low-resolution C-scan image generated cannot be used to assess spot welding quality reliably. Based on bicubic image interpolation, the C-scan image in low resolution with the large step length 1 000 ~xm is subdivided and reconstructed. By this means, the C-scan image resolution is greatly enhanced and testing results obtained are satisfactory, realizing rapid assessment of spot welds. The results of rapid ultrasonic C-scan test fit the actual metallographic measured value well. Mean value of normal distribution of error statistics is O. 006 67, and the standard deviation is O. 087 11. Rapid ultrasonic C-scan test based on image interpolation is of high accuracy and excellent stability.

EDGE-DIRECTED INTERPOLATION BASED ON SHIFTED-LINEAR IMAGE MODEL

This paper presents a hybrid image interpolation algorithm to keep details and edges simultaneously. The basic idea is to separate the unknown pixels into two classes and estimate them in different way. One class of unknown pixels is obtained via shifted linear interpolation and the other class through statistical signal processing method. The merit of this hybrid algorithm is that each unknown pixel can be estimated through original pixels simultaneously. Simulation results demonstrate that this hybrid interpolation algorithm improves the quality of the interpolated images over conventional interpolation methods.

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.

A review on image-based rendering

Image-based rendering is important both in the field of computer graphics and computer vision,and it is also widely used in virtual reality technology.For more than two decades,people have done a lot of work on the research of image-based rendering,and these methods can be divided into two categories according to whether the geometric information of the scene is utilized.According to this classification,we introduce some classical methods and representative methods proposed in recent years.We also compare and analyze the basic principles,advantages and disadvantages of different methods.Finally,some suggestions are given for research directions on image-based rendering techniques in the future.

Dynamic Data Updating Algorithm for Image Superresolution Reconstruction

A dynamic data updating algorithm for image superesolution is proposed. On the basis of Delaunay triangulation and its local updating property, this algorithm can update the changed region directly under the circumstances that only a part of the source images has been changed. For its high efficiency and adaptability, this algorithm can serve as a fast algorithm for image superesolution reconstruction.

Multimodality image registration and fusion using neural network

Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.

Research and Application of Log Defect Detection and Visualization System Based on Dry Coupling Ultrasonic Method

In order to optimize the wood internal quality detection and evaluation system and improve the comprehensive utilization rate of wood,this paper invented a set of log internal defect detection and visualization system by using the ultrasonic dry coupling agent method.The detection and visualization analysis of internal log defects were realized through log specimen test.The main conclusions show that the accuracy,reliability and practicability of the system for detecting the internal defects of log specimens have been effectively verified.The system can make the edge of the detected image smooth by interpolation algorithm,and the edge detection algorithm can be used to detect and reflect the location of internal defects of logs accurately.The content mentioned above has good application value for meeting the requirement of increasing demand for wood resources and improving the automation level of wood nondestructive testing instruments.

Study on the vehicle license plate tilt correction

The shortage of current different approaches of the vehicle license plate(VLP) tilt correction is analyzed in the paper and a new rotary correction method put forward based on the former ways of the VLP tilt correction in the horizontal direction and the vertical direction Owing to the VLP tilt taking place in the vertical direction,the array of the image’s pixels of the same column is broken,and even different rows come into being superposition.The VLP tilt taking place in the horizontal direction,by which the array of the image’s pixels of the same row broken,and so much as different columns come into being superposition.