Showing papers on "Image scaling published in 1999"

Regularity-preserving image interpolation

Abstract: Assumptions about image continuity lead to oversmoothed edges in common image interpolation algorithms. A wavelet-based interpolation method that imposes no continuity constraints is introduced. The algorithm estimates the regularity of edges by measuring the decay of wavelet transform coefficients across scales and preserves the underlying regularity by extrapolating a new subband to be used in image resynthesis. The algorithm produces visibly sharper edges than traditional techniques and exhibits an average peak signal-to-noise ratio (PSNR) improvement of 2.5 dB over bilinear and bicubic techniques.

Warped distance for space-variant linear image interpolation

Abstract: The problem of image interpolation using linear techniques is dealt with in this paper. Conventional space-invariant methods are revisited and changed into space-variant ones, by introducing the concept of the warped distance among the pixels of an image. A better perceptual rendition of the image details is obtained in this way; this effect is proved both via the evaluation of the response to an idealized sigmoidal edge model and with experiments on real-world images. The computational costs of the proposed approach are very small when compared to those of state-of-the art nonlinear interpolation operators.

Image interpolation using neural networks

Abstract: This work presents an image interpolation method based on a multilayer perceptron. The method is tested in noise-free as well as noisy line doubling and image expansion problems. Two adaptive algorithms are compared. Results show that the proposed method improves image interpolation.

Text enhancement in digital video using multiple frame integration

Abstract: In this paper a multiple frame based technique to enhance text in digital video is presented. After extracting a reference text block, we use an image matching technique to find the corresponding text blocks in consecutive frames. We register these text blocks to subpixel levels by using image interpolation techniques to improve both correspondence and text resolution. The registered text blocks are averaged to obtain a new text block with a clean background and a higher resolution. Experiments conducted on several video sequences show that our enhancement scheme can improve the accuracy of commercial off-the-shelf OCR considerably.

Method for temporal interpolation of an image sequence using object-based image analysis

Abstract: A method for temporal interpolation of an image sequence using object-based image analysis is disclosed. The method comprises the steps of image segmentation for partitioning a known image into objects, motion estimation, object-based motion field processing, determination of object depth order, detection of covered areas and newly exposed areas, adaptive interpolation using motion projection, and graceful degradation for alleviating remaining visible artifacts. The method produces interpolated images of high quality in real time for every type of image areas including fast moving objects, covered areas, and newly exposed areas.

Image interpolation by joint view triangulation

Abstract: Creating novel views by interpolating prestored images or view morphing has many applications in visual simulation. We present in this paper a new method of automatically interpolating two images which tackles two most difficult problems of morphing due to the lack of depth informational pixel matching and visibility handling. We first describe a quasi-dense matching algorithm based on region growing with the best first strategy for match propagation. Then, we describe a robust construction of matched planar patches using local geometric constraints encoded by a homography. After that we introduce a novel representation, joint view triangulation, for visible and half-occluded patches in two images to handle their visibility during the creation of new view. Finally we demonstrate these techniques on real image pairs.

Method of kernel selection for image interpolation

Abstract: A method of interpolating image data is disclosed. The method accesses a first set of discrete sample values of the image data and calculates kernel values for each of the discrete sample values using one of a plurality of kernels. The kernel is selected depending upon an edge orientation indicator, an edge strength indicator, and an edge context indicator for each of the discrete sample values. The calculated kernel values are convolved with the discrete sample values to provide a second set of discrete sample values.

Enhancement by image-dependent warping

Abstract: All image warping algorithms to date are image-independent, namely, relate only to the geometry of the image plane, ignoring the content of the image. We show that taking the image content into account yields elaborate warping schemes which may be used to enhance, sharpen and scale images. Sharpening the image is achieved by "squashing" the pixels in edge areas, and "stretching" the pixels in flat areas. Since image pixels are only moved, not modified, some drawbacks of classical linear filtering methods are avoided. We also lay the mathematical foundation for the use of an image-dependent warping scheme in traditional warping applications, such as distortion minimization.

A task-specific evaluation of three-dimensional image interpolation techniques

Abstract: Image interpolation is an important operation that is widely used in medical imaging, image processing and computer graphics. A variety of interpolation methods are available in the literature. However, their systematic evaluation is lacking. In a previous paper (ibid., vol. 15, pp. 881-92, Dec. 1996), we presented a framework for the task-independent comparison of interpolation methods based on certain image-derived figures of merit using a variety of medical image data pertaining to different parts of the human body taken from different modalities. In this work, we present an objective task-specific framework for evaluating interpolation techniques. The task considered is how the interpolation methods influence the accuracy of quantification of the total volume of lesions in the brain of multiple sclerosis (MS) patients. 60 lesion detection experiments coming from ten patient studies, two subsampling techniques and the original data, and three interpolation methods were carried out, along with a statistical analysis of the results.

Image interpolation for progressive transmission by using radial basis function networks

Abstract: Investigates the application of a radial basis function network (RBFN) to hierarchical image coding for progressive transmission. The RBFN is then used to generate an interpolated image from the subsampled version. An efficient method of computing the network parameters is developed for reduction in computational and memory requirements. The coding method does not suffer from problems of blocking effect and can produce the coarsest image quickly. Quantization error effects introduced at one stage are considered in decoding images at the following stages, thus allowing lossless progressive transmission.

Tree-Based Resolution Synthesis.

Abstract: In this paper, we present an approach to optimal image scaling called Tree-Based Resolution synthesis (TBRS). TBRS works by first performing a fast local classification of a window around the pixel being interpolated, and then by applying an interpolation filter designed for the selected class. The idea behind TBRS is to use a regression tree as a piecewise linear approximation to the conditional mean estimator of the high-resolution image given the lowresolution image. We generate the parameters for the regression tree by training on sample images. The training is computationally demanding, but it only needs to be performed once. We will demonstrate that the resulting predictor may be used effectively on input images that were not used in the training.

Method and apparatus for improved image interpolation

Abstract: A method and apparatus for image interpolation provides a simple method that can up-scale an image in various scale ratios, including fractional scaling ratios, and can yield a sharp image with reduced unpleasant visual artifacts. An embodiment uses a power weight function that is gradient dependent and uses a function that has a linear dependence on the distance to compute interpolated pixels. A further embodiment uses a power that can be adapted according to the local contrast of edges.

Improved quality of re-sliced MR images using re-normalized sinc interpolation.

Abstract: This article shows that re-normalizing the interpolation kernel for a constant integral can make a significant improvement in performance of sinc interpolation methods. A comparison was performed between standard and re-normalized sinc kernels of various sizes using data from four commonly used magnetic resonance (MR) imaging sequences. Standard rotations were performed and compared with a "gold standard" data set generated by use of a large (13 x 13 x 13) sinc kernel. Measurements of systematic pixel intensity offset error and variance of generated residuals were used to estimate resultant interpolation error. Theoretical estimates of the consequent savings in computation time were compared with the measured time required for each algorithm and with the automated image registration (AIR) program. The use of a small (5 x 5 x 5) re-normalized kernel produced relative errors comparable to those in the gold standard data set, allowing saving in computation time of up to 30 times in comparison with standard sinc interpolation. This approach brings the implementation of MR volume re-slicing much closer to the demands of a clinical environment. J. Magn. Reson. Imaging 1999;10:582-588.

High-resolution digital resampling using vector rational filters

Abstract: Rational filters are extended to multichannel signal process- ing and applied to image interpolation. Two commonly used decimation schemes are considered: a rectangular grid and a quincunx grid. For each decimation lattice, we propose a number of adaptive resampling algorithms based on the vector rational filter (VRF). These algorithms exhibit desirable properties such as edge and detail preservation and accurate chromaticity estimation. In these approaches, color image pix- els are considered as three-component vectors in the color space. Therefore, the inherent correlation that exists between the different color components is not ignored. This leads to better image quality compared to that obtained by componentwise or marginal processing. Extensive simulations show that multichannel image processing with the proposed algorithms (VRFL) and (VRFd) based on l p-norm and directional pro- cessing, respectively; significantly outperform linear and some nonlinear techniques, e.g., vector FIR median hybrid filters (VFMH). Some images interpolated using VRFL and VRFd are presented for qualitative compari- son. These images are free from blockiness and jaggedness, confirming the quantitative results. © 1999 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(99)00105-1)

High-speed, high-accuracy binarization method for recognizing text in images of low spatial resolutions

Abstract: We propose a new high-speed, high-accuracy binarization method for recognizing text in document images. First character neighborhoods are extracted from input images using a global thresholding value that is shifted to the background pixel value from the thresholding value of conventional global binarization. Second, characters are extracted using an original local binarization process integrated with image interpolation. Our method takes only 1/100 the processing time over the method that performs image interpolation first. Therefore our method binarizes an A4 size text image (150dpi) in an average of only 3.3 seconds using a 166 MHz Pentium processor. Furthermore, our method reduced unrecognized characters by 46.5%, compared with conventional global binarization.

An image resolution enhancing technique using adaptive sub-pixel interpolation for digital still camera system

Abstract: An image resolution enhancing technique is described. It is based on extracting 1-dimensional characteristic curves from subsequent frames and sub-pixel displacement values. Through sub-pixel mapping and adaptive interpolation, a high-resolution image can be obtained from several low-resolution image frames. This 1-dimensional algorithm is simple and cost-effective, and can be easily applied in real-time processing for digital still camera application.

Image processing method, image processor and storage medium

Abstract: PROBLEM TO BE SOLVED: To provide an image processing method, an image processor and a storage medium by which color noise reduction processing to effectively conduct color noise reduction processing, noise reduction processing at image compression, lightness correction processing, color saturation correction processing and image scaling processing can be executed. SOLUTION: In the image processing method where at least either correction processing in the lightness correction processing and the color saturation correction processing and the color noise reduction processing are conducted, the color noise reduction processing and the correction processing are processed in a specific sequence.

Shape-based grey-level image interpolation.

Abstract: The three-dimensional (3D) object data obtained from a CT scanner usually have unequal sampling frequencies in the x-, y- and z-directions. Generally, the 3D data are first interpolated between slices to obtain isotropic resolution, reconstructed, then operated on using object extraction and display algorithms. The traditional grey-level interpolation introduces a layer of intermediate substance and is not suitable for objects that are very different from the opposite background. The shape-based interpolation method transfers a pixel location to a parameter related to the object shape and the interpolation is performed on that parameter. This process is able to achieve a better interpolation but its application is limited to binary images only. In this paper, we present an improved shape-based interpolation method for grey-level images. The new method uses a polygon to approximate the object shape and performs the interpolation using polygon vertices as references. The binary images representing the shape of the object were first generated via image segmentation on the source images. The target object binary image was then created using regular shape-based interpolation. The polygon enclosing the object for each slice can be generated from the shape of that slice. We determined the relative location in the source slices of each pixel inside the target polygon using the vertices of a polygon as the reference. The target slice grey-level was interpolated from the corresponding source image pixels. The image quality of this interpolation method is better and the mean squared difference is smaller than with traditional grey-level interpolation.

Method and device for multi-viewpoint image interpolation

Abstract: PROBLEM TO BE SOLVED: To solve the problem that an interpolated image deteriorates in picture quality since depth-of-field information or parallax information found from images differing in viewpoint is necessary as well as the image for multi- viewpoint image interpolation for interpolating an image at an arbitrary viewpoint from the images and the depth-of-field information or parallax information is absent or has an error owing to an error in vector search or occlusion. SOLUTION: Depth-of-field information with high precision is obtained by smoothing (2) depth-of-field information through weighting minimizing a weighting function defined for a curved surface obtained from depth-of-field information and also obtaining (3) weighting information needed for the mentioned weighting at the time of the smoothing by using an index indicating the certainty of the value of the depth-of-field information and the obtained depth-of-field information with the high precision is used to interpolates (4) an image at an arbitrary viewpoint from the images differing in viewpoints.

Method and apparatus for zooming digital images

Abstract: A method and apparatus for magnifying a portion of a digital image on a display screen in either of two ways. The first method includes a two pass scheme, where each of the passes represents an interpolation in x and y direction respectively, cubic interpolation in each direction is approximated using a one dimensional convolution filter followed by linear interpolation. The second method uses a two dimensional convolution filter first, followed by bilinear interpolation. All of the procedures that are used are accelerated using a hardware package which facilitates exceptionally fast execution.

Motion field estimation by vector rational interpolation for error concealment purposes

Abstract: A study on the use of vector rational interpolation for the estimation of erroneously received motion fields of an MPEG-2 coded video bitstream has been performed. Four different motion vector interpolation schemes have been examined using motion information from available top and bottom adjacent blocks since left or right neighbours are usually lost. The presented interpolation schemes are capable of adapting their behaviour according to neighbouring motion information. Simulation results prove the satisfactory performance of the novel nonlinear interpolation schemes and the success of their application to the concealment of predictively coded frames. The motion vector rational interpolation concealment method proves to be a fast method, thus adequate for real-time applications.

Evaluation of polynomial image deformation using anatomical landmarks for matching of 3D-abdominal MR-images and for atlas construction

Abstract: While a variety of different deformation algorithms have been implemented for matching of skull, few attempts in matching areas in abdomen have been reported. In this study the authors evaluate the usability of first and second order polynomial 3D-warping for this purpose. They match abdominal MR-images from different individuals using manually picked anatomical landmarks. Generation of transformation coefficients was done through a linear regression technique that employs a least square fit using the reference landmarks. The landmarks were picked in a predefined order, well spread over the entire data set, by a radiologist. The image resampling was done using linear interpolation and the evaluation was performed visually as well as by calculating the cross correlation and the normalized least squared error between the original image and the transformed image. The authors' preliminary results reveal that the second order polynomial transformation using landmarks is a robust and efficient method. It is also superior to the second order one, for image deformation in the abdominal region and it may be used in atlas generation as well as in multimodality image co-registration and fusion.

Steerable kernel for image interpolation

Abstract: A method of providing a representation of image data is disclosed. The method accesses a plurality of discrete sample values of the image data and determines an angle of orientation of the sample values. Kernel values for each of the discrete sample values are then calculated using one of a plurality of first kernels, depending upon the angle of orientation of the discrete sample value. The first kernels are constructed by rotating a second kernel from a first angle of orientation to a second angle of orientation. Finally, the kernel values are convolved with the discrete sample values to provide a representation of said image data.

Interpolation processor and storage medium recording interpolation processing program

Abstract: PROBLEM TO BE SOLVED: To execute interpolation processing while suppressing the generation of a false color in a color image having high space frequency or an area having the high space frequency in the color image by providing the interpolation processor with a similarity decision means, an interpolation quantity calculation means for calculating the interpolation quantity of a pixel to be interpolated in accordance with the decision result of the similarity decision means or the like. SOLUTION: An optical image acquired by a photographing optical system 12 is applied to an image pickup part 13. An output from the image pickup part 13 is quantized by an A/D conversion part 14 and supplied to an image processing part 15 as the picture data of a color image. The picture data supplied to the image processing part 15 are interpolated by deciding the intensity of similarity in plural directions by using the similarity in plural directions which is calculated by a similarity calculation means, based on a similarity decision means of an interpolation processing part 17, and calculating the interpolation quantity of the pixel to be interpolated in accordance with the decision result by an interpolation quantity calculation means and recorded through a recording part 16.

Subunity coordinate translation with Fourier transform to achieve efficient and quality three-dimensional medical image interpolation.

Abstract: A new approach to the interpolation of three-dimensional (3D) medical images is presented. Instead of going through the conventional interpolation scheme where the continuous function is first reconstructed from the discrete data set and then resampled, the interpolation is achieved with a subunity coordinate translation technique. The original image is first transformed into the spatial-frequency domain. The phase of the transform is then modified with n-1 linear phase terms in the axial direction to achieve n-1 subunity coordinate translations with a distance 1/n, where n is an interpolation ratio, following the phase shift theorem of Fourier transformation. All the translated images after inverse Fourier transformation are then interspersed in turn into the original image. Since windowing plays an important role in the process, different window functions have been studied and a proper recommendation is provided. The interpolation quality produced with the present method is as good as that with the sampling (sinc) function, while the efficiency, thanks to the fast Fourier transformation, is very much improved. The approach has been validated with both computed tomography (CT) and magnetic resonance (MR) images. The interpolations of 3D CT and MR images are demonstrated.

Keyframe animation of articulated figures using autocollision-free interpolation

Abstract: Keyframing is a popular method for animating articulated figures because it allows artistic expressiveness by providing control to the animator. The animator defines a movement by providing a set of poses. The motion is then obtained by simply interpolating between these keyframes, typically with cubic splines. The drawback of this process is that it requires significant effort from the animator. Defining a movement often requires a high level of detail to ensure that the interpolation curves induce the desired motion. In particular, the animator has to focus on avoiding collisions between the limbs of his or her articulated figure. The paper describes a new interpolation method producing autocollision-free paths. A first interpolation is computed using any classical inbetweening method. Autocollisions are then identified and corrected if necessary. At some collision times, autocollision-free sub-keyframes are automatically generated using geometric properties. They are then used for obtaining an autocollision-free interpolation. Experimental results using a human model show that the animator can reduce the level of detail needed for describing a movement and still get realistic results at interactive speeds.

Fast high quality interpolation of missing data in image sequences using a controlled pasting scheme

Abstract: An important topic in image restoration is interpolation of missing data in image sequences. Missing data is a result of dirt on film and of ageing processes where the film contents are replaced by data that bears little relationship with the original scene. We present a method for interpolating missing data with the aim of achieving higher fidelity and more consistency in the interpolated results than can be achieved by existing methods. This is done by combining autoregressive models and Markov-random field techniques. Experimental results confirm the superior performance of the proposed method over existing methods.

Towards Automatic Interpolation for Real and Distant Image Pairs

Abstract: Image-based rendering offers the advantage of being able to provide realistic output and at the same time to avoid the difficult problem of a complete geometric and photometric modeling of the real world. The method described here is able to deal with non rigid scenes and large camera motions. We present in this report a three step algorithm for the interpolation of two views of a scene, from which we can for instance simulated a camera motion withing the given scene. The first step establishes pixel correspondenc- es between the images and is the most difficult part. We justify the choice of region-growing based dense matching methods and we summarize their principle. Secondly, a robust algorithm converts these pixel correspondences to an adequate structure for the last step: image interpolation. This structure encompasses the transformation between the images using constrained and dependent triangulations in both of them, and handles the half-occluded areas. The implementation of the whole process is outlined and the process is demonstrated on real images.

High quality image restoration by adaptively transformed sampling function

Abstract: We propose a method for enlarging images with high quality. The method is based on gray level interpolation, and instead of employing the general sampling function, it uses a two-dimensional sampling function, which is generated from a more appropriate function for gray level interpolation. One of the largest problems we face upon image enlargement is the exaggeration of the jagged edges. To deal with this problem, we first search for the edges and detect their direction. The two-dimensional sampling function is then transformed along the direction of these detected edges. To test for its effectiveness, the proposed method is implemented and is applied to actual image data.