Showing papers on "Bicubic interpolation published in 2007"
TL;DR: It is shown that the curvature of the interpolated isophotes is reduced, and, thus, zigzagging artifacts are largely suppressed.
Abstract: We propose an isophote-oriented, orientation-adaptive interpolation method. The proposed method employs an interpolation kernel that adapts to the local orientation of isophotes, and the pixel values are obtained through an oriented, bilinear interpolation. We show that, by doing so, the curvature of the interpolated isophotes is reduced, and, thus, zigzagging artifacts are largely suppressed. Analysis and experiments show that images interpolated using the proposed method are visually pleasing and almost artifact free
181 citations
TL;DR: It is shown that the Kaiser window based interpolator and DD interpolation are simple, robust, and outperform the 2-D DFT based lowpass interpolation as well as several existing interpolation methods proposed in the literature.
Abstract: In this paper, we investigate several efficient interpolation techniques for pilot symbol assisted channel estimation in OFDM. The interpolation methods studied include two dimensional (2-D) separable lowpass sine interpolator with Kaiser window, 2-D separable Deslauriers-Dubuc (DD) interpolation and 2-D discrete Fourier transform (DFT) based lowpass interpolation. The performances of these interpolators are compared with those of the well known minimum mean-square error (MMSE) 2-D separable Wiener filter and the perfect channel state information. It is shown that the Kaiser window based interpolator and DD interpolation are simple, robust, and outperform the 2-D DFT based lowpass interpolation as well as several existing interpolation methods proposed in the literature. These two schemes are suitable candidates for use in 1-D and 2-D channel estimation
152 citations
TL;DR: In this paper, a Fourier transform based reconstruction algorithm for solving the inverse problem in optoacoustic imaging is presented, which improves reconstruction efficiency and image quality, but without the need of using time-consuming zero-padding.
Abstract: A novel Fourier transform based reconstruction algorithm for solving the inverse problem in optoacoustic imaging is presented, which improves reconstruction efficiency and image quality. Fourier algorithms make use of an interpolation law when signal Fourier components are mapped to source Fourier components. To overcome inadequacies affiliated with interpolation methods such as nearest neighbour, linear, cubic or spline interpolation, together with signal data zero padding, we present a regularized interpolation method based on a forward model explicitly formulated for the compactly supported signal data. Simulations performed on a digital tissue phantom reveal the potential of this novel reconstruction method, which results in images of enhanced quality but without the need of using time-consuming zero-padding.
112 citations
TL;DR: The new error-amended sharp edge (EASE) scheme, which is a modified bilinear method, has proved to result in high-resolution images having clearer and sharper edges than linear interpolation methods, for all synthetic and natural images the authors have tested.
Abstract: This paper proposes a new interpolation method, called the error-amended sharp edge (EASE) scheme, which is a modified bilinear method. In order to remove/reduce interpolation artifacts such as image blur and the checkerboard effect (ringing), EASE tries to amend the interpolation error by employing the classical interpolation error theorem in an edge-adaptive fashion. EASE is applied for image zooming by both integer and noninteger magnification factors. The new interpolation scheme has proved to result in high-resolution images having clearer and sharper edges than linear interpolation methods, for all synthetic and natural images we have tested. EASE can be implemented with ease; it turns out to be similarly efficient as cubic interpolation schemes
97 citations
TL;DR: This paper presents a fast algorithm for cubic spline interpolation, which is based on the precondition of equidistant interpolation nodes, faster and easier to implement than the often applied B-Spline approach.
Abstract: Computing numerical solutions of household's optimization, one often faces the problem of interpolating functions. As linear interpolation is not very good in fitting functions, various alternatives like polynomial interpolation, Chebyshev polynomials or splines were introduced. Cubic splines are much more flexible than polynomials, since the former are only twice continuously differentiable on the interpolation interval. In this paper, we present a fast algorithm for cubic spline interpolation, which is based on the precondition of equidistant interpolation nodes. Our approach is faster and easier to implement than the often applied B-Spline approach. Furthermore, we will show how to loosen the precondition of equidistant points with strictly monotone, continuous one-to-one mappings. Finally, we present a straightforward generalization to multidimensional cubic spline interpolation.
96 citations
TL;DR: A novel image interpolation algorithm that uses the new contourlet transform to improve the regularity of object boundaries in the generated images and significantly outperforms linear interpolation in subjective quality and in most cases, in terms of PSNR as well.
Abstract: With the ever increasing computational power of modern day processors, it has become feasible to use more
robust and computationally complex algorithms that increase the resolution of images without distorting edges
and contours. We present a novel image interpolation algorithm that uses the new contourlet transform to
improve the regularity of object boundaries in the generated images. By using a simple wavelet-based linear
interpolation scheme as our initial estimate, we use an iterative projection process based on two constraints
to drive our solution towards an improved high-resolution image. Our experimental results show that our new
algorithm significantly outperforms linear interpolation in subjective quality, and in most cases, in terms of
PSNR as well.
77 citations
TL;DR: A new heterogeneity-projection scheme based on a novel spectral-spatial correlation concept is proposed to estimate the best interpolation direction directly from the original mosaic image and perform hard-decision interpolation, in which each pixel only needs to be interpolated once.
Abstract: This paper presents a novel heterogeneity-projection hard-decision (HPHD) color interpolation procedure for reproduction of Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which each pixel only needs to be interpolated once. A new heterogeneity-projection scheme based on a novel spectral-spatial correlation concept is proposed to estimate the best interpolation direction directly from the original mosaic image. Using the proposed heterogeneity-projection scheme, a hard-decision rule can be decided before performing the interpolation. The advantage of this scheme is that it provides an efficient way for decision-based algorithms to generate improved results using fewer computations. Compared with three recently reported demosaicing techniques, Gunturk's, Lu's, and Li's methods, the proposed HPHD outperforms all of them in both PSNR values and S-CIELAB DeltaEab * measures by utilizing 25 natural images from Kodak PhotoCD
50 citations
TL;DR: In this article, a comparison between linear, distance-based and cubic interpolation schemes outlining their advantages and drawbacks in atmospheric physics, meteorology and climatology applications is presented.
36 citations
Patent•
16 Jul 2007
TL;DR: In this paper, a graphics processing unit for rendering objects from a software application executing on a processing unit in which the objects to be rendered are received as control points of bicubic surfaces is presented.
Abstract: The present invention provides a graphics processing unit for rendering objects from a software application executing on a processing unit in which the objects to be rendered are received as control points of bicubic surfaces. According to the method and system disclosed herein, the graphics processing unit includes a transform unit, a lighting unit, a renderer unit, and a tessellate unit for tessellating both rational and non-rational object surfaces in real-time.
35 citations
TL;DR: An interpolation algorithm for conversion from the interlaced to the progressive scanning format using a fuzzy rule-based edge-restoration interpolation part using the different types of edge, peak, and monotonic slope patterns.
Abstract: This paper proposes an interpolation algorithm for conversion from the interlaced to the progressive scanning format. The proposed algorithm consists of two parts: an edge direction detection part and a fuzzy rule-based edge-restoration interpolation part. The different types of edge, peak, and monotonic slope patterns are considered in a spatial domain interpolation strategy. Edges with a certain vertical component look preserved in the interpolation using a fuzzy rule-based algorithm. The vertical resolution in the interpolated image is subjectively concealed by introducing vertical gradients in the interpolation. Computer simulations verify the effective performance of this image processing technology.
35 citations
TL;DR: The rational cubic function is extended to rational bicubic partially blended function (Coons Patches) and simple constraints are derived on free parameters in the description of rational bimodal partially blended patches to visualize the monotone data in the view ofmonotone surfaces.
TL;DR: In this paper, the authors developed a dynamic multi-point rational interpolation method based on Krylov subspace techniques to generate reduced order models for passive components and interconnects that are accurate across a wide-range of frequencies.
Abstract: The efficient modeling of integrated passive components and interconnects is vital for the realization of high performance mixed-signal systems. In this paper, we develop a dynamic multi-point rational interpolation method based on Krylov subspace techniques to generate reduced order models for passive components and interconnects that are accurate across a wide-range of frequencies. We dynamically select interpolation points by applying a cubic spline-based algorithm to detect complex regions in the system's frequency response. The results indicate that our method provides greater accuracy than techniques that apply uniform interpolation points.
TL;DR: A subdivision scheme that generalizes bicubic spline subdivision to control nets with polar structure for surfaces with the combinatorial structure of objects of revolution and at points of high valence in subdivision meshes is described and analyzed.
Abstract: We describe and analyze a subdivision scheme that generalizes bicubic spline subdivision to control nets with polar structure. Such control nets appear naturally for surfaces with the combinatorial structure of objects of revolution and at points of high valence in subdivision meshes. The resulting surfaces are C2 except at a finite number of isolated points where the surface is C1 and the curvature is bounded.
27 Jun 2007
TL;DR: In this paper, a high-resolution (MR) image is reconstructed from a sequence of subpixel shifted, aliased low-resolution frames by means of a novel nonuniform interpolation super-resolution method.
Abstract: In this paper a high-resolution (MR) image is reconstructed from a sequence of subpixel shifted, aliased low-resolution (LR) frames by means of a novel nonuniform interpolation super-resolution (SR) method. A gradient-based algorithm estimates the horizontal and vertical shifts for each frame. Then, the uniformly spaced sampling points of the UK image are produced by means of Kriging interpolation. Wiener filtering is employed to deal with the restoration problem. The novelty of the proposed nonuniform interpolation approach to SR image reconstruction lies in the employment of Kriging interpolation technique. Comparisons with the original image demonstrate the superiority of our method to a conventional nonuniform interpolation one of SR image reconstruction.
TL;DR: The overall conclusion is that the multiresolution refinement algorithm based on EHD combined with the bicubic interpolation method is very robust and effective for the registration of X-ray angiography images, which can obtain sub-pixel registration accuracy and is fully automatic.
Abstract: X-ray angiography, a powerful technique for the visualization of blood vessels, has been widely used in clinical practice. However, due to unavoidable motion of patient, the subtraction images often suffer from misregistration artifacts. In order to improve the quality of subtraction images, registration algorithms are often employed before direct subtraction of mask and live images. A novel multiresolution elastic registration algorithm is proposed for the registration of the digital angiographic images using thin-plate spline (TPS). Our main contribution is a multiresolution search strategy specifically designed for the template matching method. In this strategy, the mask image is decomposed to coarse and fine sub-image blocks iteratively using the pyramid approach. Experimental results show that the multiresolution refinement strategy is well adapted to the template matching method, and can achieve better performance than comparable single step algorithms, because local minima can be overcome by the gradual coarse-to-fine approach that also ensures convergence. Registration results of four typical similarity measures, namely energy of histogram of differences (EHD), mutual information (MI), correlation and sum of squared differences (SSD), are compared. Three different interpolation methods, including nearest-neighbor, bilinear and bicubic, are also tested and compared. The overall conclusion is that the multiresolution refinement algorithm based on EHD combined with the bicubic interpolation method is very robust and effective for the registration of X-ray angiography images, which can obtain sub-pixel registration accuracy and is fully automatic. In addition, the objective measurement method developed in this paper on simulated data makes it possible to quantitatively evaluate the quality of the elastic registration results
TL;DR: In this paper, a closed spherical fractal interpolation surface is constructed based on the construction of bivariate fractal surfaces, and the interpolation takes place in spherical coordinates and with the transformation to Cartesian coordinates a closed surface arises.
30 May 2007
TL;DR: In this article, the authors proposed a nonlinear image interpolation method, based on an anisotropic diffusion PDE and designed for the general case of vector-valued images, where the interpolation solution is restricted to the subspace of functions that can recover the discrete input image, after an appropriate smoothing and sampling.
Abstract: We propose a nonlinear image interpolation method, based on an anisotropic diffusion PDE and designed for the general case of vector-valued images. The interpolation solution is restricted to the subspace of functions that can recover the discrete input image, after an appropriate smoothing and sampling. The proposed nonlinear diffusion flow lies on this subspace and its strength and anisotropy effectively adapt to the local variations and geometry of image structures. The derived model efficiently reconstructs the real image structures, leading to a natural interpolation, with reduced blurring, staircase and ringing artifacts of classic methods. This method also outperforms other existing PDE-based interpolation methods. We present experimental results that prove the potential and efficacy of the method as applied to graylevel and color images.
TL;DR: The proposed bicubic method adopts both the local asymmetry features and the local gradient features of an image in the interpolation processing to obtain high accuracy interpolated images.
Abstract: In this paper, we propose a novel bicubic method for digital image interpolation. Since the conventional bicubic method does not consider image local features, the interpolated images obtained by the conventional bicubic method often have a blurring problem. In this paper, the proposed bicubic method adopts both the local asymmetry features and the local gradient features of an image in the interpolation processing. Experimental results show that the proposed method can obtain high accuracy interpolated images.
29 Apr 2007
TL;DR: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on lowresolution images, and uses single neural network as classifier, which produces straightforward approach towards face recognition.
Abstract: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on lowresolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses backpropagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image. Keywords—Average filtering, Bicubic Interpolation, Neurons, vectorization.
TL;DR: The purpose of this paper is to provide sufficient geometric conditions that imply the existence of a cubic parametric polynomial curve which interpolates six points in the plane.
Journal Article•
23 Jul 2007-World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering
TL;DR: An image magnification using adaptive interpolation by pixel level data-dependent geometrical shapes is proposed that tries to take into account information about the edges (sharp luminance variations) and smoothness of the image.
Abstract: World has entered in 21 century. The technology of computer graphics and digital cameras is prevalent. High resolution display and printer are available. Therefore high resolution images are needed in order to produce high quality display images and high quality prints. However, since high resolution images are not usually provided, there is a need to magnify the original images. One common difficulty in the previous magnification techniques is that of preserving details, i.e. edges and at the same time smoothing the data for not introducing the spurious artefacts. A definitive solution to this is still an open issue. In this paper an image magnification using adaptive interpolation by pixel level data-dependent geometrical shapes is proposed that tries to take into account information about the edges (sharp luminance variations) and smoothness of the image. It calculate threshold, classify interpolation region in the form of geometrical shapes and then assign suitable values inside interpolation region to the undefined pixels while preserving the sharp luminance variations and smoothness at the same time. The results of proposed technique has been compared qualitatively and quantitatively with five other techniques. In which the qualitative results show that the proposed method beats completely the Nearest Neighbouring (NN), bilinear(BL) and bicubic(BC) interpolation. The quantitative results are competitive and consistent with NN, BL, BC and others. Keywords—Adaptive, digital image processing, image magnification, interpolation, geometrical shapes, qualitative & quantitative analysis.
TL;DR: Algorithms for the resizing of images based on the analysis of the sum of primary implicants representation of image data, as generated by a logical transform are presented.
Abstract: The resizing of data, either upscaling or downscaling based on need for increased or decreased resolution, is an
important signal processing technique due to the variety of data sources and formats used in today's world. Image
interpolation, the 2D variation, is commonly achieved through one of three techniques: nearest neighbor, bilinear
interpolation, or bicubic interpolation. Each method comes with advantages and disadvantages and selection of the
appropriate one is dependent on output and situation specifications. Presented in this paper are algorithms for the
resizing of images based on the analysis of the sum of primary implicants representation of image data, as generated by
a logical transform. The most basic algorithm emulates the nearest neighbor technique, while subsequent variations
build on this to provide more accuracy and output comparable to the other traditional methods. Computer simulations
demonstrate the effectiveness of these algorithms on binary and grayscale images.
Patent•
27 Jul 2007
TL;DR: In this article, a linear pixel clock is used to determine the position of a pixel in a 2D image, and displayed pixel intensities are determined using interpolation techniques, where nonlinear image scan trajectories such as sinusoidal and bi-sinusoidal trajectories are accommodated.
Abstract: An image generation apparatus provides interpolation and distortion correction. The interpolation and distortion correction may be provided in one or two dimensions. Nonlinear image scan trajectories, such as sinusoidal and bi-sinusoidal trajectories are accommodated. Horizontal and vertical scan positions are determined using a linear pixel clock, and displayed pixel intensities are determined using interpolation techniques.
TL;DR: In this article, the authors compare Models-3/Community Multiscale Air Quality (CMAQ) outputs at multiple resolutions by interpolating from coarse resolution to fine resolution and analyzing the interpolation difference.
TL;DR: The cubic B-spline, angular interpolation was preferable to either sinc or linear interpolation methods, and the reduction of background artifacts improves lineshape fitting.
Abstract: Spectral-spatial imagesreconstructed from a small number of projections suffer from streak artifacts that are seen as noise, particularly in the spectral dimension. Interpolation in projection space can reduce artifacts in the reconstructed images. The reduction of background artifacts improves lineshape fitting. In this work, we compared the performances of angular interpolation implemented using linear, cubic B-spline, and sinc methods. Line width maps were extracted from 4-D EPRimages of phantoms using spectral fitting to evaluate each interpolation method and its robustness to noise. Results from experiment and simulation showed that the cubic B-spline, angular interpolation was preferable to either sinc or linear interpolation methods.
Patent•
26 Sep 2007
TL;DR: In this paper, the authors proposed a motion compensated video interpolation method in which the interpolation step varies according to the amplitude and/or a reliability index of the estimated motion vector for the considered pixel.
Abstract: The invention proposes a motion compensated video interpolation that is not sensitive to the errors in the motion estimation vectors. The invention proposes a motion compensated video interpolation method in which the interpolation step varies according to the amplitude and/or a reliability index of the estimated motion vector for the considered pixel. The number of pixels to be taken into account for interpolation and the weighting factors associated with these pixels are made to vary according to the amplitude and/or reliability index of the estimated motion vector.
TL;DR: A trivariate Lagrange interpolation method based on C 1 cubic splines is described, which is local and stable, provides optimal order approximation, and has linear complexity.
Abstract: A trivariate Lagrange interpolation method based on C 1 cubic splines is described. The splines are defined over a special refinement of the Freudenthal partition of a cube partition. The interpolating splines are uniquely determined by data values, but no derivatives are needed. The interpolation method is local and stable, provides optimal order approximation, and has linear complexity.
12 Nov 2007
TL;DR: Simulation and comparison results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity.
Abstract: This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. Consequently, the local edge directions are represented by length-16 vectors, which are denoted as weight vectors. The weight vectors are used to formulate geometric regularity constraint, which is imposed on the interpolated image through the Markov Random Field (MRF) model. Furthermore, the interpolation problem is formulated as a Maximum A Posterior (MAP)-MRF problem and, under the MAP-MRF framework, the desired interpolated image corresponds to the minimal energy state of a two-dimensional random held. Simulated Annealing method is used to search for the minimal energy state from a reasonable large state space. Simulation and comparison results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity.
24 Sep 2007
TL;DR: In this article, a novel edge-adaptive image interpolation method was proposed, which is easy to implement and computationally efficient, but none of them are comparable to classical interpolation methods such as Bi-linear interpolation or Bi-cubic interpolation concerning computational cost.
Abstract: In this paper we propose a novel edge-adaptive interpolation method which is easy to implement and computationally efficient. Although various edge-adaptive image interpolation methods have been proposed in the past, none of them are comparable to classical interpolation methods such as Bi-linear interpolation or Bi-cubic interpolation concerning computational cost. Here we propose a novel interpolation method modifying the classical interpolation methods adaptive to improve the quality around the edges. The proposed method's flow is the following: 1) For all pixels, determine the local gradient defined by plane approximation of four neighbouring pixels. 2) Derive the edge-adaptive interpolation kernel by edge-directed interpolation axes. 3) Interpolate. From the results of experiments, the effectiveness of the proposed method concerning the computational cost and subjective image quality have been verified.