Showing papers on "Image scaling published in 1998"

An axiomatic approach to image interpolation

Abstract: We discuss possible algorithms for interpolating data given in a set of curves and/or points in the plane. We propose a set of basic assumptions to be satisfied by the interpolation algorithms which lead to a set of models in terms of possibly degenerate elliptic partial differential equations. The absolute minimal Lipschitz extension model (AMLE) is singled out and studied in more detail. We show experiments suggesting a possible application, the restoration of images with poor dynamic range.

Software pixel interpolation for digital still cameras suitable for a 32-bit MCU

Abstract: This paper discusses the interpolation technique applied to the Bayer primary color method, used frequently as the pixel structure of CCD image sensors for digital still cameras. Eight typical types of interpolation methods are discussed from three viewpoints: the characteristics of the interpolated images, the processing time required to realize their methods based on a 32-bit MCU for embedded applications, and the quality of the resultant images. In terms of reducing the occurrences of pseudocolor and achieving good color restoration, the linear interpolation method taking G's correlation determined by using R/B pixels into consideration was found to be excellent. The measured machine cycle of the interpolation methods was approximately 46 cycles per pixel. Therefore, every method was able to interpolate a VGA-size image in approximately 0.2 seconds with the MCU operating at 60 MHz. In terms of the S/N ratio, a good image quality was obtained through the linear interpolation methods, even with shorter processing time. Based on these results it is concluded that the linear interpolation method, which takes correlation into consideration, is the most suitable for consumer product applications such as digital still cameras.

Image scaling circuit for fixed pixed resolution display

Abstract: An image scaling circuit for increasing or decreasing the size of a sampled image to match a fixed resolution display. The circuit includes means for resizing the image in the horizontal and vertical dimension using independent sample rate converters. The sample rate converters increase or decrease the image size by a factor of Lx/Mx in the horizontal dimension and Ly/My in the vertical dimension where Lx and Ly are integers and Mx and My are decimal numbers of arbitrary precision to provide fine scaling control. In addition, image warping is conveniently implemented by varying the down sample ratios Mx and My on a pixel by pixel and/or line by line basis.

Interpolation device, process and recording medium on which interpolation processing program is recorded

Abstract: An interpolation device performs interpolation of an image in which grid points that output a predetermined color and empty grid points that do not output the predetermined color are arrayed in a checkered configuration A recording medium stores an image interpolation processing program A first similarity calculator calculates a first vertical direction similarity and a first horizontal direction similarity A second similarity calculator calculates a second vertical direction similarity and a second horizontal direction similarity A similarity calculator determines the similarity in the vertical direction of an empty grid point based on the first vertical similarity and the second horizontal similarity and determines the similarity in the horizontal direction of the empty grid point based on the first horizontal similarity and the second horizontal similarity An interpolation amount calculator calculates an interpolation amount, by selecting the pixel output of grid point(s) positioned in a direction with a strong similarity, or by weight-adding the pixel outputs of the grid points positioned in the vertical direction and the horizontal direction, according to the similarities that are determined

POCS based adaptive image magnification

Abstract: We tackle the problem of magnifying an image without incurring blurring, ringing or other artifacts common to classical schemes. The proposed iterative scheme starts with an initial magnified image generated by a process of selective interpolation. By placing suitable constraints on the final magnified image, which are convex in nature, we show that magnification can be posed as a problem of finding a solution which lies at the intersection of convex sets. By avoiding explicit high frequency enhancing assumptions in the iterative process, we avoid edge enhancement artifacts in the magnified image.

Visibility sorting and compositing without splitting for image layer decompositions

Abstract: We present an efficient algorithm for visibility sorting a set of moving geometric objects into a sequence of image layers which are composited to produce the final image. Instead of splitting the geometry as in previous visibility approaches, we detect mutual occluders and resolve them using an appropriate image compositing expression or merge them into a single layer. Such an algorithm has many applications in computer graphics; we demonstrate two: rendering acceleration using image interpolation and visibility-correct depth of field using image blurring. We propose a new, incremental method for identifying mutually occluding sets of objects and computing a visibility sort among these sets. Occlusion queries are accelerated by testing on convex bounding hulls; less conservative tests are also discussed. Kd-trees formed by combinations of directions in object or image space provide an initial cull on potential occluders, and incremental collision detection algorithms are adapted to resolve pairwise occlusions, when necessary. Mutual occluders are further analyzed to generate an image compositing expression; in the case of nonbinary occlusion cycles, an expression can always be generated without merging the objects into a single layer. Results demonstrate that the algorithm is practical for real-time animation of scenes involving hundreds of objects each comprising hundreds or thousands of polygons. CR Categories: I.3.3 [Computer Graphics]: Picture/Image Generation Display algorithms. Additional

Adaptive diagonal interpolation for image resolution enhancement

Abstract: A method or device for increasing the resolution of an image generates additional pixels in the image using interpolation. Various tests are performed for each additional pixel to determine whether conditions render the interpolation direction ambiguous or uncertain. In a television image, for example, an interpolation direction is derived for each additional pixel from a weighted combination of a vertical direction and a best-choice diagonal direction. If a potential interpolation condition cannot be determined with a high level of confidence, the weighted combination favors the vertical direction.

A run-time reconfigurable engine for image interpolation

Abstract: Custom Computing Machines (CCM's) have demonstrated significant performance advantages over general-purpose processors for certain classes of problems. However, problems can always be found which require computational resources in excess of those available on a particular CCM. Exploiting the reconfigurable nature of FPGAs can alleviate this limitation. The FPGAs' computational resources can be time multiplexed to allow different portions of the computation to execute in stages. Intermediate results are saved to memory and passed on to later stages of the computation. This technique is used in this work to implement an image interpolation engine on the Xilinx XC6264 Reference Board. The engine utilizes 2-5-2 splines to take advantage of their computationally convenient powers-of-two arithmetic.

Motion compensation image interpolation—frame rate conversion for HDTV

Abstract: A process for up-converting an existing video source signal having a low frequency (frames/second) to a high frequency signal for use with High Definition Television (HDTV). The process samples the existing frames in the existing video signal and calculates integer displacements of pels within the existing frames. A polynomial curve fit is then performed on the displacements to obtain estimates of horizontal and vertical displacements of each block in each existing frame. Based on the alignment of the blocks within a sampling grid on each frame, the blocks are segregated into groups. The block groups are then used to interpolate missing or required frames of the high frequency signal in a piecemeal manner by utilizing blocks of a particular block group to estimate a corresponding block in a frame of the high frequency signal.

Design of practical color filter array interpolation algorithms for digital cameras .2

Abstract: For pt.1 see Proceeding of SPIE, vol.3028, p.117-25, SPIE, Bellingham, WA, 1997. Single-chip digital cameras use a color filter array and subsequent interpolation strategy to produce full-color images. While the design of the interpolation algorithm can be grounded in traditional sampling theory, the fact that the sampled data is distributed among three different color planes adds a level of complexity. Existing interpolation methods are usually derived from general numerical methods that do not make many assumptions about the nature of the data. Significant computational economies, without serious losses in image quality can be achieved if it is recognized that the data is image data and some appropriate image model is assumed.

View interpolation for image synthesis

Abstract: Image-space simplifications have been used to accelerate the calculation of computer graphic images since the dawn of visual simulation. Texture mapping has been used to provide a means by which images may themselves be used as display primitives. The work reported by this paper endeavors to carry this concept to its logical extreme by using interpolated images to portray three-dimensional scenes. The special-effects technique of morphing, which combines interpolation of texture maps and their shape, is applied to computing arbitrary intermediate frames from an array of prestored images. If the images are a structured set of views of a 3D object or scene, intermediate frames derived by morphing can be used to approximate intermediate 3D transformations of the object or scene. Using the view interpolation approach to synthesize 3D scenes has two main advantages. First, the 3D representation of the scene may be replaced with images. Second, the image synthesis time is independent of the scene complexity. The correspondence between images, required for the morphing method, can be predetermined automatically using the range data associated with the images. The method is further accelerated by a quadtree decomposition and a view-independent visible priority. Our experiments have shown that the morphing can be performed at interactive rates on today’s high-end personal computers. Potential applications of the method include virtual holograms, a walkthrough in a virtual environment, image-based primitives and incremental rendering. The method also can be used to greatly accelerate the computation of motion blur and soft shadows cast by area light sources. CR Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/Image Generation; I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism. Additional Keywords: image morphing, interpolation, virtual reality, motion blur, shadow, incremental rendering, real-time display, virtual holography, motion compensation.

Apparatus and method of building an electronic database for resolution synthesis

Abstract: An electronic database for image interpolation is generated by a computer. The computer generates a low-resolution image from a training image, a plurality of representative vectors from the low-resolution image, and a plurality of interpolation filters corresponding to each of the representative vectors. The interpolation filters and the representative vectors are generated off-line and can be used to perform image interpolation on an image other than the training image. The database can be stored in a device such as computer or a printer.

Regularized Interative Image Interpolation and its application to Spatially Scalable Coding

Abstract: This paper presents a regularized iterative image interpolation algorithm, which can restore high frequency details in the original high resolution image In order to apply the regularization approach to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system According to the model, we propose a regularization based spatial image sequence interpolation algorithm and apply the proposed algorithm to a spatially scalable coding

Efficient algorithm and architecture for image scaling using discrete wavelet transforms

Abstract: What is disclosed is an image scaling technique and apparatus. The technique and apparatus utilizes a discrete wavelet transform (DWT). The DWT is applied row-wise to an image, which results in a low frequency sub-band and a high frequency sub-band. The DWT is again applied column-wise to the result of the row-wise DWT. The end result is a 2:1 scaled image. The process may be modified easily to obtain a 4:1 scaled image. Further, the architecture for computing the DWT provides high throughput and is composed, due to the nature of the DWT of address multipliers, registers and delay elements.

Method and system for adaptive video image resolution enhancement

Abstract: A system (1) for enhancing the resolution of a video image by a predetermined enhancement factor is provided. System (1) generally includes an interpolation subsystem (10), a data storage module (20), and a pixel insert positioning module (30). Included within interpolation subsystem (10) are a classification module (100), a bilinear interpolation module (200), and an adaptive interpolation module (300). Classification module (100) receives the original image pixels in a specified field of the given video image and designates for each original image pixels it receives one of a plurality of predefined classifications. Based upon this classification, one of the bilinear interpolation (200) and adaptive interpolation (300) modules is selected for actuation in generating the supplementary image pixels necessary to support resolution enhancement. Adaptive interpolation module (300) employs an interpolation scheme adapted for the orientation of a given image portion detected by classification module (100) through a plurality of adaptation parameters which, once generated, may be stored within data storage module (20) to promote computational efficiency. The generated supplementary image pixels may then be inserted at the pixel insert positions generated by pixel insert positioning module (30) in accordance with the given enhancement factor to form a resolution enhanced image.

Classification -based method in optimal image interpolation

Abstract: Atkins, C. Brian. Ph.D., Purdue University, December 1998. Classification-Based Methods in Optimal Image Interpolation. Major Professors: Charles A. Bouman and Jan P. Allebach. In this thesis, we introduce two new approaches to optimal image interpolation which are based on the idea that image data falls into different categories or classes, such as edges of different orientation and smoother gradients. Both these methods work by first classifying the image data in a window around the pixel being interpolated, and then using an interpolation filter designed for the selected class. The first method, which we call Resolution Synthesis (RS), performs the classification by computing probabilities of class membership in a Gaussian mixture model. The second method, which we call Tree-based Resolution Synthesis (TRS), uses a regression tree. Both of these methods are based on stochastic models for image data whose parameters must have been estimated beforehand, by training on sample images. We demonstrate that under some assumptions, both of these methods are actually optimal in the sense that they yield minimum mean-squared error (MMSE) estimates of the target-resolution image, given the source image. We also introduce Enhanced Tree-based RS, which consists of TRS interpolation followed by an enhancement stage. During the enhancement stage, we recursively add adjustments to the pixels in the interpolated image. This has the dual effect of reducing interpolation artifacts while imparting additional sharpening. We present results of the above methods for interpolating images which are free of artifacts. In addition, we present results which demonstrate that RS can be trained for high-quality interpolation of images which

A new digital signal processor for progressive scan CCD

Abstract: A digital signal processor, which is dedicated to the PS-CCD (progressive scan type CCD), is developed. The DSCP1 (Digital Still Camera Processor 1) adopts a new pixel interpolation algorithm which takes an average of two mean pixel values from the 4 neighboring pixels and an individual color matrix before gamma control in order to provide the higher image quality. The DSCP1 also provides a scan conversion from the progressive scan to the interlace scan type image without requiring a specific video memory to achieve a moving picture function.

View synthesis by trinocular edge matching and transfer

Abstract: This paper presents a novel automatic method for view synthesis (or image transfer) from a triplet of uncalibrated images based on trinocular edge matching followed by transfer by interpolation, occlusion detection and correction and finally rendering. The edge-based technique proposed here is of general practical relevance because it overcomes most of the problems encountered in other approaches that either rely upon dense correspondence, work in projective space or need explicit camera calibration. Applications range from immersive media and teleconferencing, image interpolation for fast rendering and compression.

A generalized interpolative VQ method for jointly optimal quantization and interpolation of images

Abstract: We discuss the problem of reconstruction of a high resolution image from a lower resolution image by a jointly optimum interpolative vector quantization method. The interpolative vector quantizer maps quantized low dimensional 2/spl times/2 image blocks to higher dimensional 4/spl times/4 blocks by a table lookup method. As a special case of generalized vector quantization (GVQ), a jointly optimal quantizer and interpolator (GIVQ) is introduced to find the corresponding code books for the low and high resolution image. In order to incorporate the nearest neighborhood constraint on the quantizer and also to obtain the desired distortion in the interpolated image, a deterministic annealing based optimization technique has been applied. With a small interpolation example, we demonstrate the superior performance of this method over nonlinear interpolative vector quantization (NLIVQ), in which the interpolator is optimized for a given input quantizer.

High quality digital scaling using pixel window averaging and linear interpolation

Abstract: A system and method for selective scaling of an image by selective implementation of a window averaging processing technique or an interpolation processing technique. For enlargement scaling, the interpolation processor is implemented. For reduction scaling, the window averaging processor is implemented. For anamorphic scaling, the window averaging processor may be selected and implemented for reduction processing pursuant to a two-pass processing technique wherein the interpolator processing will be implemented thereafter.

Scanner line interpolation device

Abstract: There is provided a scanning line interpolation device which is capable of providing an interpolated image with increased reproducibility of vertical high-frequency components in a still picture part. Preceding-field image data is stored in a field memory, and thereafter reference pixels which are located in an interpolation pixel position and its surrounding positions and required for interpolation are extracted from the preceding-field image data stored in the field memory and current-field image data. An inter-field motion judgement portion detects whether or not there is a motion of an image between preceding and current fields based on the extracted reference pixels. If the inter-field motion judgement portion detects that there is a motion, a selection circuit selects in-field interpolation data calculated in an in-field interpolation value calculation circuit from the current-field image data among the reference pixels. If the inter-field judgement portion detects that there is no motion, the selection circuit selects the preceding-field image data located in the interpolation pixel position among the reference pixels. Then, the selection circuit outputs the selected data as interpolation pixel image data.

Interpolation filtering method for accurate sub-pixel motion assessment

Abstract: In order to generate an improved image signal in motion assessment, an exact pixel determination of a moving vector is initially carried out, followed by a two-step interpolation filtering at exact subpixel resolution The interpolation coefficients are chosen with the purpose of reducing aliasing A larger number of adjacent pixels are used in comparison with conventional interpolation methods The quality of the prediction signal for moving images can be thus improved, thereby enhancing coding efficiency

Image interpolation using unions of spheres

Abstract: volumetric model of an image. The technique requires little preprocessing and is not labour-intensive. It allows the user a reasonable degree of control of the matching process. Our method easily facilitates intuitive manual specification of features where desired. The results of our tests are very positive. The problems encountered in using our algorithm are largely predictable and suggest definite directions for future work.

Method and apparatus for image scaling during printing

Abstract: In a computing system where there is more than one printer, a user first formats an image to fit a first printable area for a first medium on a first printer. This image when printed with the same format on a second printer on a medium with a smaller printable area will result in a clipped image. A printer system is modified to include a method to determine a scaling factor. The printer system uses this scaling factor to convert dimension-related information in a set of print data which defines the original image. The resultant print data after conversion is used to print an image on the second printable area. This image has a format which is proportional to the format of the original image.

Color image interpolation using vector rational filters

Abstract: Rational filters are extended to multichannel signal processing and applied to the image interpolation problem. The proposed nonlinear interpolator exhibits desirable properties, such as, edge and details preservation. In this approach the pixels of the color image are considered as 3-component vectors in the color space. Therefore, the inherent correlation which exists between the different color components is not ignored; thus, leading to better image quality than those obtained by component-wise processing. Simulations show that the resulting edges obtained using vector rational filters (VRF) are free from blockiness and jaggedness, which are usually present in images interpolated using especially linear, but also some nonlinear techniques, e.g. vector median hybrid filters (VFMH).

Image interpolation apparatus

Abstract: For enabling image enlargement or reduction of high image quality with improved definition, there is disclosed an image interpolating device comprising a memory for storing digital image signal, memory readout means for reading pixel data in succession from the memory, first, second and third consecutive delay means for respectively delaying the image signal S n , read by the memory readout means, to respectively from pixel signals S n−1 , S n−2 , S n−3 , first, second, third and fourth coefficient generation circuits for generating interpolation coefficients respectively corresponding to the pixel signals S n , S n−1 , S n−2 , S n−3 and determined by N-th order functions from the position of the interpolated pixel S′ positioned between the pixel signals S n−1 and S n−2 , and a signal synthesis circuit for calculating the sum of respective product of pixel signal S n and interpolation coefficient k n .

Image scaling processing device and image scaling processing method

Abstract: The image scaling processing device distinguishes whether an original image data is a character image or a half-tone image per a pixel unit in the image domain separating portion and scales each image in the character scaling processing portion and the half-tone scaling processing portion. In order to get a desired scale factor L times image data, the character scaling processing is performed by the first scaling processing for enlarging an image data by 2 n times (n is an integer, L 2 n ) in each sub scanning direction and main scanning direction and by the second scaling processing for enlarging by L/2 n times the image data enlarged by 2 n times.

Improved Classification Robustness for Noisy Cell Images Represented as Principal-Component Projections in a Hybrid Recognition System

Abstract: Different types of cells are recognized from their noisy images by use of a hybrid recognition system that consists of a learning principal-component analyzer and an image-classifier network. The inputs to the feed-forward backpropagation classifier are the first 15 principal components of the 10 x 10 pixel image to be classified. The classifier was trained with clear images of cells in metaphase, unburst cells, and other erroneous patterns. Experimental results show that the recognition system is robust to image scaling and rotation, as well as to image noise. Cell recognition is demonstrated for images that are corrupted with additive Gaussian noise, impulse noise, and quantization errors. We compare the performance of the hybrid recognition system with that of a conventional three-layer feed-forward backpropagation network that uses the raw image directly as input.

CCD data pixel interpolation circuit and digital still camera equipped with it

Abstract: A pixel interpolation circuit in the digital still camera according to the present invention, filters unnecessary pixel data from pixel data read out from a CCD which has captured an image, and stores only necessary pixel data for a pixel interpolation operation, in a dual-port data buffer. At the same time, the pixel interpolation circuit reads out necessary data for the pixel interpolation operation, from the data buffer, performs the pixel interpolation operation, and stores the result in a video memory. The pixel interpolation operation is performed by weighting pixels to be used for the pixel-interpolation operation, in accordance with the distance between a pixel to be interpolated and each of the to-be-weighted pixels.

Three-dimensional reconstruction from cone-beam data using an efficient Fourier technique combined with a special interpolation filter

Abstract: We here present LINCON(FAST) which is an exact method for 3D reconstruction from cone-beam projection data. The new method is compared to the LINCON method which is known to be fast and to give good image quality. Both methods have O(N3 log N) complexity and are based on Grangeat's result which states that the derivative of the Radon transform of the object function can be obtained from cone-beam projections. One disadvantage with LINCON is that the rather computationally intensive chirp z-transform is frequently used. In LINCON(FAST), FFT and interpolation in the Fourier domain are used instead, which are less computationally demanding. The computation tools involved in LINCON(FAST) are solely FFT, 1D eight-point interpolation, multiplicative weighting and tri-linear interpolation. We estimate that LINCON(FAST) will be 2-2.5 times faster than LINCON. The interpolation filter belongs to a special class of filters developed by us. It turns out that the filter must be very carefully designed to keep a good image quality. Visual inspection of experimental results shows that the image quality is almost the same for LINCON and the new method LINCON(FAST). However, it should be remembered that LINCON(FAST) can never give better image quality than LINCON, since LINCON(FAST) is designed to approximate LINCON as well as possible.