Showing papers on "Image resolution published in 2001"

Permanent scatterers in SAR interferometry

Abstract: Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of the results. The authors present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images. When, as it often happens, the dimension of the PS is smaller than the resolution cell, the coherence is good even for interferograms with baselines larger than the decorrelation one, and all the available images of the ESA ERS data set can be successfully exploited. On these pixels, submeter DEM accuracy and millimetric terrain motion detection can be achieved, since atmospheric phase screen (APS) contributions can be estimated and removed. Examples are then shown of small motion measurements, DEM refinement, and APS estimation and removal in the case of a sliding area in Ancona, Italy. ERS data have been used.

A new approach for the morphological segmentation of high-resolution satellite imagery

Abstract: A new segmentation method based on the morphological characteristic of connected components in images is proposed. Theoretical definitions of morphological leveling and morphological spectrum are used in the formal definition of a morphological characteristic. In multiscale segmentation, this characteristic is formalized through the derivative of the morphological profile. Multiscale segmentation is particularly well suited for complex image scenes such as aerial or fine resolution satellite images, where very thin, enveloped and/or nested regions must be retained. The proposed method performs well in the presence of both low radiometric contrast and relatively low spatial resolution. Those factors may produce a textural effect, a border effect, and ambiguity in the object/background distinction. Segmentation examples for satellite images are given.

Deriving intrinsic images from image sequences

Abstract: Intrinsic images are a useful midlevel description of scenes proposed by H.G. Barrow and J.M. Tenenbaum (1978). An image is de-composed into two images: a reflectance image and an illumination image. Finding such a decomposition remains a difficult problem in computer vision. We focus on a slightly, easier problem: given a sequence of T images where the reflectance is constant and the illumination changes, can we recover T illumination images and a single reflectance image? We show that this problem is still imposed and suggest approaching it as a maximum-likelihood estimation problem. Following recent work on the statistics of natural images, we use a prior that assumes that illumination images will give rise to sparse filter outputs. We show that this leads to a simple, novel algorithm for recovering reflectance images. We illustrate the algorithm's performance on real and synthetic image sequences.

Thin Observation Module by Bound Optics (TOMBO): Concept and Experimental Verification

Abstract: A compact image-capturing system called TOMBO (an acronym for thin observation module by bound optics) is presented in which the compound-eye imaging system is utilized to achieve a thin optical configuration. The captured multiple images are processed to retrieve the image of the target object. For image retrieval, two kinds of processing method are considered: image sampling and backprojection. Computer simulations and preliminary experiments were executed on an evaluation system to verify the principles of the system and to clarify the issues related to its implementation.

Midcourse Space Experiment Survey of the Galactic Plane

Abstract: The Midcourse Space Experiment (MSX) surveyed the entire Galactic plane within |b| ≤ 5° in four mid-infrared spectral bands between 6 and 25 μm at a spatial resolution of ~183. The survey was redundant within |b| ≤ 45 with four-fold coverage over two-thirds of the area. These survey data were combined to create 1680 15 × 15 images that cover the region with 6'' pixel spacing in each of the spectral bands. The images preserve the inherent resolution of the data but have up to twice the sensitivity of a single scan. The individual survey observations had to be extensively conditioned to achieve the co-add advantage. The noise equivalent radiance (NER) at 8.3 μm, the most sensitive MSX mid-infrared spectral band, varies from ~1.3 MJy sr-1 in the inner Galaxy to 3 times that at the latitude limits in the outer Galaxy; the sensitivities of the other MSX mid-infrared bands are 10–25 times less. Additionally, 36 lower resolution 10° × 10° images were generated in each band that span the full latitude and longitude range of the survey. These panoramic images have a resolution of ~12 with 36'' pixel spacing and a six-fold improvement in NER, making them an ideal product for comparison with radio surveys of the Galactic plane. An ancillary set of images has been created from other MSX astronomy experiments that lie within 10° of the Galactic plane. These images either extend the latitude coverage of the survey or provide deeper probes of Galactic structure either by themselves or when added to the survey images.

Robust super-resolution

Abstract: A robust approach for super-resolution is, presented, which is especially valuable in the presence of outliers. Such outliers may be due to motion errors, inaccurate blur models, noise, moving objects, motion blur etc. This robustness is needed since super-resolution methods are very sensitive to such errors. A robust median estimator is combined in an iterative process to achieve a super resolution algorithm. This process can increase resolution even in regions with outliers, where other super resolution methods actually degrade the image.

Image formation in phase-shifting digital holography and applications to microscopy

Abstract: We discuss image formation in phase-shifting digital holography by developing an analytical formulation based on the Fresnel-Kirchhoff diffraction theory. Image-plane position and imaging magnification are derived for general configurations in which a spherical reference is employed. The influences of discrete sampling of the resulting interference patterns by a CCD and numerical reconstruction on qualities of point images are investigated. Dependence of the point images on the ratio of the minimum fringe spacing to pixel pitch of the CCD is numerically analyzed. Two-point resolution and magnification are also investigated as a function of pixel numbers by a simulation using a one-dimensional model. In experiments magnified images of biological objects and a resolution target were reconstructed with the same quality as by conventional microscopy.

Generalized multi-dimensional adaptive filtering for conventional and spiral single-slice, multi-slice, and cone-beam CT.

Abstract: In modern computed tomography (CT) there is a strong desire to reduce patient dose and/or to improve image quality by increasing spatial resolution and decreasing image noise. These are conflicting demands since increasing resolution at a constant noise level or decreasing noise at a constant resolution level implies a higher demand on x-ray power and an increase of patient dose. X-ray tube power is limited due to technical reasons. We therefore developed a generalized multi-dimensional adaptive filtering approach that applies nonlinear filters in up to three dimensions in the raw data domain. This new method differs from approaches in the literature since our nonlinear filters are applied not only in the detector row direction but also in the view and in the z-direction. This true three-dimensional filtering improves the quantum statistics of a measured projection value proportional to the third power of the filter size. Resolution tradeoffs are shared among these three dimensions and thus are considerably smaller as compared to one-dimensional smoothing approaches. Patient data of spiral and sequential single- and multi-slice CT scans as well as simulated spiral cone-beam data were processed to evaluate these new approaches. Image quality was assessed by evaluation of difference images, by measuring the image noise and the noise reduction, and by calculating the image resolution using point spread functions. The use of generalized adaptive filters helps to reduce image noise or, alternatively, patient dose. Image noise structures, typically along the direction of the highest attenuation, are effectively reduced. Noise reduction values of typically 30%-60% can be achieved in noncylindrical body regions like the shoulder. The loss in image resolution remains below 5% for all cases. In addition, the new method has a great potential to reduce metal artifacts, e.g., in the hip region.

Rigid registration of 3-D ultrasound with MR images: a new approach combining intensity and gradient information

Abstract: Presents a new image-based technique to rigidly register intraoperative three-dimensional ultrasound (US) with preoperative magnetic resonance (MR) images. Automatic registration is achieved by maximization of a similarity measure which generalizes the correlation ratio, and whose novelty is to incorporate multivariate information from the MR data (intensity and gradient). In addition, the similarity measure is built upon a robust intensity-based distance measure, which makes it possible to handle a variety of US artifacts. A cross-validation study has been carried out using a number of phantom and clinical data. This indicates that the method is quite robust and that the worst registration errors are of the order of the MR image resolution.

Retinal thickness measurements from optical coherence tomography using a Markov boundary model

Abstract: Presents a system for detecting retinal boundaries in optical coherence tomography (OCT) B-scans. OCT is a relatively new imaging modality giving cross-sectional images that are qualitatively similar to ultrasound. However, the axial resolution with OCT is much higher, on the order of 10 /spl mu/m. Objective, quantitative measures of retinal thickness may be made from OCT images. Knowledge of retinal thickness is important in the evaluation and treatment of many ocular diseases. The boundary-detection system presented here uses a one-dimensional edge-detection kernel to yield edge primitives. These edge primitives are rated, selected, and organized to form a coherent boundary structure by use of a Markov model of retinal boundaries as detected by OCT. Qualitatively, the boundaries detected by the automated system generally agreed extremely well with the true retinal structure for the vast majority of OCT images. Only one of the 1450 evaluation images caused the algorithm to fail. A quantitative evaluation of the retinal boundaries was performed as well, using the clinical application of automatic retinal thickness determination. Retinal thickness measurements derived from the algorithm's results were compared with thickness measurements from manually corrected boundaries for 1450 test images. The algorithm's thickness measurements over a 1-mm region near the fovea differed from the corrected thickness measurements by less than 10 /spl mu/m for 74% of the images and by less than 25 /spl mu/m (10% of normal retinal thickness) for 98.4% of the images. These errors are near the machine's resolution limit and still well below clinical significance. Current, standard clinical practice involves a qualitative, visual assessment of retinal thickness. A robust, quantitatively accurate system such as the authors' can be expected to improve patient care.

Performance evaluation of the microPET P4: a PET system dedicated to animal imaging.

Abstract: The microPET Primate 4-ring system (P4) is an animal PET tomograph with a 7.8 cm axial extent, a 19 cm diameter transaxial field of view (FOV) and a 22 cm animal port. The system is composed of 168 detector modules, each with an 8×8 array of 2.2×2.2×10 mm3 lutetium oxyorthosilicate crystals, arranged as 32 crystal rings 26 cm in diameter. The detector crystals are coupled to a Hamamatsu R5900-C8 PS-PMT via a 10 cm long optical fibre bundle. The detectors have a timing resolution of 3.2 ns, an average energy resolution of 26%, and an average intrinsic spatial resolution of 1.75 mm. The system operates in 3D mode without inter-plane septa, acquiring data in list mode. The reconstructed image spatial resolution ranges from 1.8 mm at the centre to 3 mm at 4 cm radial offset. The tomograph has a peak system sensitivity of 2.25% at the centre of the FOV with a 250-750 keV energy window. The noise equivalent count rate peaks at 100-290 kcps for representative object sizes. Images from two phantoms and three different types of laboratory animal demonstrate the advantage of the P4 system over the original prototype microPET, including its threefold improvement in sensitivity and a large axial FOV sufficient to image an entire mouse in a single bed position.

Calculating dense disparity maps from color stereo images, an efficient implementation

Abstract: This paper presents an efficient implementation for correlation based stereo. Research in this area can roughly be divided in two classes: improving accuracy regardless of computing time and scene reconstruction in real-time. Algorithms achieving video frame rates must have strong limitations in image size and disparity search range, whereas high quality results often need several minutes per image pair. This paper tries to fill the gap, it provides instructions how to implement correlation based disparity calculation with high speed and reasonable quality that can be used in a wide range of applications or to provide an initial solution for more sophisticated methods. Left-right consistency checking and uniqueness validation are used to eliminate false matches. Optionally, a fast median filter can be applied to the results to further remove outliers. Source code will be made publicly available as contribution to the Open Source Computer Vision Library, further acceleration with SIMD instructions is planned for the near future.

Super-resolution target identification from remotely sensed images using a Hopfield neural network

Abstract: Fuzzy classification techniques have been developed recently to estimate the class composition of image pixels, but their output provides no indication of how these classes are distributed spatially within the instantaneous field of view represented by the pixel. As such, while the accuracy of land cover target identification has been improved using fuzzy classification, it remains for robust techniques that provide better spatial representation of land cover to be developed. Such techniques could provide more accurate land cover metrics for determining social or environmental policy, for example. The use of a Hopfield neural network to map the spatial distribution of classes more reliably using prior information of pixel composition determined from fuzzy classification was investigated. An approach was adopted that used the output from a fuzzy classification to constrain a Hopfield neural network formulated as an energy minimization tool. The network converges to a minimum of an energy function, defined as a goal and several constraints. Extracting the spatial distribution of target class components within each pixel was, therefore, formulated as a constraint satisfaction problem with an optimal solution determined by the minimum of the energy function. This energy minimum represents a "best guess" map of the spatial distribution of class components in each pixel. The technique was applied to both synthetic and simulated Landsat TM imagery, and the resultant maps provided an accurate and improved representation of the land covers studied, with root mean square errors (RMSEs) for Landsat imagery of the order of 0.09 pixels in the new fine resolution image recorded.

Relationship of light scattering at an angle in the backward direction to the backscattering coefficient

Abstract: We revisit the problem of computing the backscattering coefficient based on the measurement of scattering at one angle in the back direction. Our approach uses theory and new observations of the volume scattering function (VSF) to evaluate the choice of angle used to estimate bb. We add to previous studies by explicitly treating the molecular backscattering of water (bbw) and its contribution to the VSF shape and to bb. We find that there are two reasons for the tight correlation between observed scattering near 120° and the backscattering coefficient reported by Oishi [Appl. Opt.29, 4658, (1990)], namely, that (1) the shape of the VSF of particles (normalized to the backscattering) does not vary much near that angle for particle assemblages of differing optical properties and size, and (2) the ratio of the VSF to the backscattering is not sensitive to the contribution by water near this angle. We provide a method to correct for the water contribution to backscattering when single-angle measurements are used in the back direction (for angles spanning from near 90° to 160°) that should provide improved estimates of the backscattering coefficient.

Image reconstruction and enhanced resolution imaging from irregular samples

Abstract: While high resolution, regularly gridded observations are generally preferred in remote sensing, actual observations are often not evenly sampled and have lower-than-desired resolution. Hence, there is an interest in resolution enhancement and image reconstruction. This paper discusses a general theory and techniques for image reconstruction and creating enhanced resolution images from irregularly sampled data. Using irregular sampling theory, we consider how the frequency content in aperture function-attenuated sidelobes can be recovered from oversampled data using reconstruction techniques, thus taking advantage of the high frequency content of measurements made with nonideal aperture filters. We show that with minor modification, the algebraic reconstruction technique (ART) is functionally equivalent to Grochenig's (1992) irregular sampling reconstruction algorithm. Using simple Monte Carlo simulations, we compare and contrast the performance of additive ART, multiplicative ART, and the scatterometer image reconstruction (SIR) (a derivative of multiplicative ART) algorithms with and without noise. The reconstruction theory and techniques have applications with a variety of sensors and can enable enhanced resolution image production from many nonimaging sensors. The technique is illustrated with ERS-2 and SeaWinds scatterometer data.

A novel high resolution, wide swath SAR system

Abstract: A novel SAR system architecture is presented. It allows to combine a high azimuth resolution with a wide imaged swath width. The architecture and the required on board signal processing is described. Finally two examples systems and their image performance are presented.

Image transformation and synthesis methods

Abstract: In a telepresence system, a scene is captured by recording pixel data elements, each associated with a pixel ray vector having a direction and an intercept on an known locus in the frame of reference of the scene. Each pixel data element includes data representing the illumination along the pixel ray vector. For example, the pixel data elements may be captured by operating numerous video cameras pointing in different directions on a spherical locus. A virtual viewpoint image representing the image which would be seen from an arbitrary viewpoint, looking in an arbitrary direction, can be synthesized by determining the directions of synthetic pixel ray vectors from each pixel of the virtual viewpoint image through the virtual viewpoint and the intercepts of these vectors on the locus. Recorded pixel data elements having pixel ray vector directions and intercepts close to those of the synthetic pixel ray vector can be copied or interpolated to provide data representing illumination in the synthetic pixel.

Multiscale MAP filtering of SAR images

Abstract: Synthetic aperture radar (SAR) images are disturbed by a multiplicative noise depending on the signal (the ground reflectivity) due to the radar wave coherence. Images have a strong variability from one pixel to another reducing essentially the efficiency of the algorithms of detection and classification. We propose to filter this noise with a multiresolution analysis of the image. The wavelet coefficient of the reflectivity is estimated with a Bayesian model, maximizing the a posteriori probability density function. The different probability density function are modeled with the Pearson system of distributions. The resulting filter combines the classical adaptive approach with wavelet decomposition where the local variance of high-frequency images is used in order to segment and filter wavelet coefficients.

Strain rate imaging using two-dimensional speckle tracking

Abstract: Strain rate images (SRI) of the beating heart have been proposed to identify non-contracting regions of myocardium. Initial attempts used spatial derivatives of tissue velocity (Doppler) signals. Here, an alternate method is proposed based on two-dimensional phase-sensitive speckle tracking applied to very high frame rate, real-time images. This processing can produce high resolution maps of the time derivative of the strain magnitude (i.e., square root of the strain intensity). Such images complement traditional tissue velocity images (TVI), providing a more complete description of cardiac mechanics. To test the proposed approach, SRI were both simulated and measured on a thick-walled, cylindrical, tissue-equivalent phantom modeling cardiac deformations. Real-time ultrasound images were captured during periodic phantom deformation, where the period was matched to the data capture rate of a commercial scanner mimicking high frame rate imaging of the heart. Simulation results show that SRI with spatial resolution between 1 and 2 mm are possible with an array system operating at 5 MHz. Moreover, these images are virtually free of angle-dependent artifacts present in TVI and simple strain rate maps derived from these images. Measured results clearly show that phantom regions of low deformation, which are difficult to identify on tissue velocity-derived SRI, are readily apparent with SRI generated from two-dimensional phase-sensitive speckle tracking.

Advances in pulsed thermography

Abstract: The use of pulsed thermography as an NDE solution for manufacturing and in-service applications has increased dramatically in the past five years, enabled by advances in IR camera and computer technology. However, the basic approaches to analysis and processing of pulsed thermographic data have remained largely unchanged. These methods include image averaging, subtraction, division, slope calculation and contrast methods (e.g. peak contrast and peak slope time mapping). We have developed an alternative approach to analysis of pulsed thermographic data, based on developing a parametric equation for the time history of each pixel. The resulting synthetic image provides increased spatial and temporal resolution, and significantly extends the range of defect depths and sample configurations to which pulsed thermography can be applied. In addition, our approach reduces the amount of data that must be manipulated and stored, so that an entire array of image sequences from a large structure can be processed simultaneously.

Resolution limits for infrared microspectroscopy explored with synchrotron radiation

Abstract: The spatial resolution for infrared microspectroscopy is investigated to determine the practical limits imposed by diffraction or optical aberrations. Quantitative results are obtained using high brightness synchrotron radiation, which serves as a diffraction-limited infrared “point source” for the microscope. The measured resolving power is in good agreement with diffraction theory, including a ∼ 30% improvement for a confocal optical arrangement. The diffraction calculation also shows how the confocal setup leads to better image contrast. The full width at half maximum of the instrument’s resolution pattern is approximately λ/2 for this arrangement. One achieves this diffraction limit when the instrument’s apertures define a region having dimensions equal to the wavelength of interest. While commercial microspectrometers are well corrected for optical aberrations (allowing diffraction-limited results), the standard substrates used for supporting specimens introduce chromatic aberrations. An analysis of ...

Giant magnetoresistance-based eddy-current sensor

Abstract: The purpose of this paper is to introduce a new eddy-current testing technique for surface or near-surface defect detection in nonmagnetic metals using giant magnetoresistive (GMR) sensors. It is shown that GMR-based eddy-current probes are able to accurately detect short surface-breaking cracks in conductive materials. The self-rectifying property of the GMR sensor used in this study leads to a simplified signal conditioning circuit, which can be fully integrated on a silicon chip with the GMR sensor. The ability to manufacture probes having small dimensions and high sensitivity (220 mV/mT) to low magnetic fields over a broad frequency range (from dc up to 1 MHz) enhances the spatial resolution of such an eddy-current testing probe. Experimental results obtained by scanning two different probes over a slotted aluminum specimen are presented. General performance characteristics are demonstrated by measurements of surface and subsurface defects of different sizes and geometries. Dependence of the sensor output on orientation, liftoff distance, and excitation intensity is also investigated.

Optimal image scaling using pixel classification

Abstract: We introduce a new approach to optimal image scaling called resolution synthesis (RS). In RS, the pixel being interpolated is first classified in the context of a window of neighboring pixels; and then the corresponding high-resolution pixels are obtained by filtering with coefficients that depend upon the classification. RS is based on a stochastic model explicitly reflecting the fact that pixels falls into different classes such as edges of different orientation and smooth textures. We present a simple derivation to show that RS generates the minimum mean-squared error (MMSE) estimate of the high-resolution image, given the low-resolution image. The parameters that specify the stochastic model must be estimated beforehand in a training procedure that we have formulated as an instance of the well-known expectation-maximization (EM) algorithm. We demonstrate that the model parameters generated during the training may be used to obtain superior results even for input images that were not used during the training.

Procedure to detect anatomical structures in optical fundus images

Abstract: We present an overview of the design and test of an image processing procedure for detecting all important anatomical structures in color fundus images. These structures are the optic disk, the macula and the retinal network. The algorithm proceeds through five main steps: (1) automatic mask generation using pixels value statistics and color threshold, (2) visual image quality assessment using histogram matching and Canny edge distribution modeling, (3) optic disk localization using pyramidal decomposition, Hausdorff-based template matching and confidence assignment, (4) macula localization using pyramidal decomposition and (5) bessel network tracking using recursive dual edge tracking and connectivity recovering. The procedure has been tested on a database of about 40 color fundus images acquired from a digital non-mydriatic fundus camera. The database is composed of images of various types (macula- and optic disk-centered) and of various visual quality (with or without abnormal bright or dark regions, blurred, etc).© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Electronic imaging using a logarithmic asphere.

Abstract: Transmission functions are derived that are valid in the nonparaxial case for a class of lenses that will image a continuum of points along an optical axis to a single image point This lens, which we call a logarithmic asphere, is then used in a digital camera The resolution of the camera is limited by the pixel size of the CCD; ie, it is not diffraction limited Digital processing is used to recover the image, and image-plane processing is used for speed We find a tenfold increase in the depth of field over that for the diffraction-limited case

Second-order accurate particle image velocimetry

Abstract: An adaptive, second-order accurate particle image velocimetry (PIV) technique is presented. The technique uses two singly exposed images that are interrogated using a modified cross-correlation algorithm. Consequently, any of the equipment commonly available for conventional PIV (such as dual head Nd: YAG lasers, interline transfer CCD cameras, etc.) can be used with this more accurate algorithm. At the heart of the algorithm is a central difference approximation to the flow velocity (accurate to order Δt 2) versus the forward difference approximation (accurate to order Δt) common in PIV. An adaptive interrogation region-shifting algorithm is used to implement the central difference approximation. Adaptive shifting algorithms have been gaining popularity in recent years because they allow the spatial resolution of the PIV technique to be maximized. Adaptive shifting algorithms also have the virtue of helping to eliminate velocity bias errors. The second- order accuracy resulting from the central difference approximation can be obtained with relatively little additional computational effort compared to that required for a standard first-order accurate forward difference approximation. The adaptive central difference interrogation (CDI) algorithm has two main advantages over adaptive forward difference interrogation (FDI) algorithms: it is more accurate, especially at large time delays between camera exposures; and it provides a temporally symmetric view of the flow. By comparing measurements of flow around a single red blood cell made using both algorithms, the CDI technique is shown to perform better than conventional FDI-PIV interrogation algorithms near flow boundaries. Cylindrical Taylor–Couette flow images, both experimental and simulated, are used to demonstrate that the CDI algorithm is significantly more accurate than conventional PIV algorithms, especially as the time delay between exposures is increased. The results of the interrogations are shown to agree quite well with analytical predictions and confirm that the CDI algorithm is indeed second-order accurate while the conventional FDI algorithm is only first-order accurate.

Optimization of optode arrangements for diffuse optical tomography: A singular-value analysis

Abstract: We develope a method to optimize the resolution of diffuse optical tomographic instruments. Singular-value analysis of the tomographic weight matrix associated with specific data types, geometries, and optode arrangements is shown to provide a measure of image resolution. We achieve optimization of device configuration by monitoring the resolution measure described. We introduce this idea and demonstrate its utility by optimizing the spatial sampling interval and field-of-view parameters in the parallel-plane transmission geometry employed for diffuse optical breast imaging. We also compare resolution in transmission and remission geometries.

Initial results from the IMAGE Extreme Ultraviolet Imager

Abstract: The Extreme Ultraviolet Imager (EUV) of the IMAGE mission is providing the first global images of the He + distribution in Earth's plasmasphere. The EUV instru- ment images the He + resonance line emission at 30.4 nm at a time resolution of 10 minutes and a spatial resolution of 0.1 RE. Each image encompasses the entire plasmasphere in a single frame, to permit study of the structure and dy- namics of the plasmasphere in its entirety. Here we survey several of the most striking features of the plasmasphere as seen by EUV. These features include convection tails, de- pleted regions that we call "voids," isolated magnetic flux tubes filled to higher He + density than their neighbors, and "shoulders" in the He + distribution.

Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants

Abstract: In this paper, we propose to improve the POCS-based super-resolution reconstruction (SRR) methods in two ways. First, the discretization of the continuous image formation model is improved to explicitly allow for higher order interpolation methods to be used. Second, the constraint sets are modified to reduce the amount of edge ringing present in the high resolution image estimate. This effectively regularizes the inversion process.

Method and apparatus for transmission and display of a compressed digitized image

Abstract: The present technique selectively handles image data, which is decomposed into a plurality of resolution levels. In one embodiment, an image resolution suitable for display in a desired viewport is selected via an iterative process including determining whether scaling of one of the different image resolutions of the plurality of different image resolutions by a predetermined scaling threshold would result in a scaled image resolution that is less than or equal to the resolution of the desired viewport. A portion of the plurality of data sets may be selectively requested for recomposition of the image at the image resolution. Additional systems, methods, and devices for handling image data are also disclosed.