Showing papers on "Image resolution published in 2006"

Reversible data hiding

Abstract: A novel reversible data hiding algorithm, which can recover the original image without any distortion from the marked image after the hidden data have been extracted, is presented in this paper. This algorithm utilizes the zero or the minimum points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. It can embed more data than many of the existing reversible data hiding algorithms. It is proved analytically and shown experimentally that the peak signal-to-noise ratio (PSNR) of the marked image generated by this method versus the original image is guaranteed to be above 48 dB. This lower bound of PSNR is much higher than that of all reversible data hiding techniques reported in the literature. The computational complexity of our proposed technique is low and the execution time is short. The algorithm has been successfully applied to a wide range of images, including commonly used images, medical images, texture images, aerial images and all of the 1096 images in CorelDraw database. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed algorithm.

Digital camera identification from sensor pattern noise

Abstract: In this paper, we propose a new method for the problem of digital camera identification from its images based on the sensor's pattern noise. For each camera under investigation, we first determine its reference pattern noise, which serves as a unique identification fingerprint. This is achieved by averaging the noise obtained from multiple images using a denoising filter. To identify the camera from a given image, we consider the reference pattern noise as a spread-spectrum watermark, whose presence in the image is established by using a correlation detector. Experiments on approximately 320 images taken with nine consumer digital cameras are used to estimate false alarm rates and false rejection rates. Additionally, we study how the error rates change with common image processing, such as JPEG compression or gamma correction.

"Finite-Element" Displacement Fields Analysis from Digital Images: Application to Portevin-Le Châtelier Bands

Abstract: A new methodology is proposed to estimate displacement fields from pairs of images (reference and strained) that evaluates continuous displacement fields. This approach is specialized to a finite-element decomposition, therefore providing a natural interface with a numerical modeling of the mechanical behavior used for identification purposes. The method is illustrated with the analysis of Portevin–Le Châtelier bands in an aluminum alloy sample subjected to a tensile test. A significant progress with respect to classical digital image correlation techniques is observed in terms of spatial resolution and uncertainty.

High-resolution ab initio three-dimensional x-ray diffraction microscopy

Abstract: Coherent x-ray diffraction microscopy is a method of imaging nonperiodic isolated objects at resolutions limited, in principle, by only the wavelength and largest scattering angles recorded. We demonstrate x-ray diffraction imaging with high resolution in all three dimensions, as determined by a quantitative analysis of the reconstructed volume images. These images are retrieved from the three-dimensional diffraction data using no a priori knowledge about the shape or composition of the object, which has never before been demonstrated on a nonperiodic object. We also construct two-dimensional images of thick objects with greatly increased depth of focus (without loss of transverse spatial resolution). These methods can be used to image biological and materials science samples at high resolution with x-ray undulator radiation and establishes the techniques to be used in atomic-resolution ultrafast imaging at x-ray free-electron laser sources.

Near-Field Microscopy Through a SiC Superlens

Abstract: The wave nature of light limits the spatial resolution in classical microscopy to about half of the illumination wavelength. Recently, a new approach capable of achieving subwavelength spatial resolution, called superlensing, was invented, challenging the already established method of scanning near-field optical microscopy (SNOM). We combine the advantages of both techniques and demonstrate a novel imaging system where the objects no longer need to be in close proxim-ity to a near-field probe, allowing for optical near-field microscopy of subsurface objects at sub-wavelength-scale lateral resolution.

Cell refractive index tomography by digital holographic microscopy.

Abstract: For what we believe to be the first time, digital holographic microscopy is applied to perform optical diffraction tomography of a pollen grain. Transmission phase images with nanometric axial accuracy are numerically reconstructed from holograms acquired for different orientations of the rotating sample; then the three-dimensional refractive index spatial distribution is computed by inverse radon transform. A precision of 0.01 for the refractive index estimation and a spatial resolution in the micrometer range are demonstrated.

Digital light field photography

Abstract: Focusing images well has been difficult since the beginnings of photography in 1839. Three manifestations of the problem are: the chore of having to choose what to focus on before clicking the shutter, the awkward coupling between aperture size and depth of field, and the high optical complexity of lenses required to produce aberration-free images. These problems arise because conventional cameras record only the sum of all light rays striking each pixel on the image plane. This dissertation presents a unified solution to these focus problems by instead recording the light field inside the camera: not just the position but also the direction of light rays striking the image plane. I describe the design, prototyping and performance of a digital camera that records this light field in a single photographic exposure. The basic idea is to use an array of microlenses in front of the photosensor in a regular digital camera. The main price behind this new kind of photography is the sacrifice of some image resolution to collect directional ray information. However, it is possible to smoothly vary the optical configuration from the light field camera back to a conventional camera by reducing the separation between the microlenses and photosensor. This allows a selectable trade-off between image resolution and refocusing power. More importantly, current semiconductor technology is already capable of producing sensors with an order of magnitude more resolution than we need in final images. The extra ray directional information enables unprecedented capabilities after exposure. For example, it is possible to compute final photographs that are refocused at different depths, or that have extended depth of field, by re-sorting the recorded light rays appropriately. Theory predicts, and experiments corroborate, that blur due to incorrect focus can be reduced by a factor approximately equal to the directional resolution of the recorded light rays. Similarly, digital correction of lens aberrations re-sorts aberrant light rays to where they should ideally have converged, improving image contrast and resolution. Future cameras based on these principles will be physically simpler, capture light more quickly, and provide greater flexibility in finishing photographs.

Fully 3-D PET reconstruction with system matrix derived from point source measurements

Abstract: The quality of images reconstructed by statistical iterative methods depends on an accurate model of the relationship between image space and projection space through the system matrix. The elements of the system matrix for the clinical Hi-Rez scanner were derived by processing the data measured for a point source at different positions in a portion of the field of view. These measured data included axial compression and azimuthal interleaving of adjacent projections. Measured data were corrected for crystal and geometrical efficiency. Then, a whole system matrix was derived by processing the responses in projection space. Such responses included both geometrical and detection physics components of the system matrix. The response was parameterized to correct for point source location and to smooth for projection noise. The model also accounts for axial compression (span) used on the scanner. The forward projector for iterative reconstruction was constructed using the estimated response parameters. This paper extends our previous work to fully three-dimensional. Experimental data were used to compare images reconstructed by the standard iterative reconstruction software and the one modeling the response function. The results showed that the modeling of the response function improves both spatial resolution and noise properties

A frequency domain approach to registration of aliased images with application to super-resolution

Abstract: Super-resolution algorithms reconstruct a high-resolution image from a set of low-resolution images of a scene. Precise alignment of the input images is an essential part of such algorithms. If the low-resolution images are undersampled and have aliasing artifacts, the performance of standard registration algorithms decreases. We propose a frequency domain technique to precisely register a set of aliased images, based on their low-frequency, aliasing-free part. A high-resolution image is then reconstructed using cubic interpolation. Our algorithm is compared to other algorithms in simulations and practical experiments using real aliased images. Both show very good visual results and prove the attractivity of our approach in the case of aliased input images. A possible application is to digital cameras where a set of rapidly acquired images can be used to recover a higher-resolution final image.

Multiframe demosaicing and super-resolution of color images

Abstract: In the last two decades, two related categories of problems have been studied independently in image restoration literature: super-resolution and demosaicing. A closer look at these problems reveals the relation between them, and, as conventional color digital cameras suffer from both low-spatial resolution and color-filtering, it is reasonable to address them in a unified context. In this paper, we propose a fast and robust hybrid method of super-resolution and demosaicing, based on a maximum a posteriori estimation technique by minimizing a multiterm cost function. The L/sub 1/ norm is used for measuring the difference between the projected estimate of the high-resolution image and each low-resolution image, removing outliers in the data and errors due to possibly inaccurate motion estimation. Bilateral regularization is used for spatially regularizing the luminance component, resulting in sharp edges and forcing interpolation along the edges and not across them. Simultaneously, Tikhonov regularization is used to smooth the chrominance components. Finally, an additional regularization term is used to force similar edge location and orientation in different color channels. We show that the minimization of the total cost function is relatively easy and fast. Experimental results on synthetic and real data sets confirm the effectiveness of our method.

A Multilevel Context-Based System for Classification of Very High Spatial Resolution Images

Abstract: This paper proposes a novel pixel-based system for the supervised classification of very high geometrical (spatial) resolution images. This system is aimed at obtaining accurate and reliable maps both by preserving the geometrical details in the images and by properly considering the spatial-context information. It is made up of two main blocks: 1) a novel feature-extraction block that, extending and developing some concepts previously presented in the literature, adaptively models the spatial context of each pixel according to a complete hierarchical multilevel representation of the scene and 2) a classifier, based on support vector machines (SVMs), capable of analyzing hyperdimensional feature spaces. The choice of adopting an SVM-based classification architecture is motivated by the potentially large number of parameters derived from the contextual feature-extraction stage. Experimental results and comparisons with a standard technique developed for the analysis of very high spatial resolution images confirm the effectiveness of the proposed system

Spatio-angular resolution tradeoffs in integral photography

Abstract: An integral camera samples the 4D light field of a scene within a single photograph. This paper explores the fundamental tradeoff between spatial resolution and angular resolution that is inherent to integral photography. Based on our analysis we divide previous integral camera designs into two classes depending on how the 4D light field is distributed (multiplexed) over the 2D sensor. Our optical treatment is mathematically rigorous and extensible to the broader area of light field research.We argue that for many real-world scenes it is beneficial to sacrifice angular resolution for higher spatial resolution. The missing angular resolution is then interpolated using techniques from computer vision. We have developed a prototype integral camera that uses a system of lenses and prisms as an external attachment to a conventional camera. We have used this prototype to capture the light fields of a variety of scenes. We show examples of novel view synthesis and refocusing where the spatial resolution is significantly higher than is possible with previous designs.

Creating 3d images of objects by illuminating with infrared patterns

Abstract: According to a general aspect, processing images includes projecting an infra-red pattern onto a three-dimensional object and producing a first image, a second image, and a third image of the three-dimensional object while the pattern is projected on the three-dimensional object. The first image and the second image include the three-dimensional object and the pattern. The first image and the second image are produced by capturing at a first camera and a second camera, respectively, light filtered through an infra-red filter. The third image includes the three-dimensional object but not the pattern. Processing the images also includes establishing a first-pair correspondence between a portion of pixels in the first image and a portion of pixels in the second image. Processing the images further includes constructing, based on the first-pair correspondence and the third image, a two-dimensional image that depicts a three-dimensional construction of the three-dimensional object.

Data driven image models through continuous joint alignment

Abstract: This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar as possible by removing variability along the known axes of variation. This technique can be used to eliminate "nuisance" variables such as affine deformations from handwritten digits or unwanted bias fields from magnetic resonance images. In addition to separating and modeling the latent images - i.e., the images without the nuisance variables - we can model the nuisance variables themselves, leading to factorized generative image models. When nuisance variable distributions are shared between classes, one can share the knowledge learned in one task with another task, leading to efficient learning. We demonstrate this process by building a handwritten digit classifier from just a single example of each class. In addition to applications in handwritten character recognition, we describe in detail the application of bias removal from magnetic resonance images. Unlike previous methods, we use a separate, nonparametric model for the intensity values at each pixel. This allows us to leverage the data from the MR images of different patients to remove bias from each other. Only very weak assumptions are made about the distributions of intensity values in the images. In addition to the digit and MR applications, we discuss a number of other uses of congealing and describe experiments about the robustness and consistency of the method.

High-resolution surface plasmon resonance sensor based on linewidth-optimized nanohole array transmittance.

Abstract: A high spectral resolution, 2D nanohole-array-based surface plasmon resonance sensor that operates at normal or near normal incidence--facilitating high spatial resolution imaging--is presented. The angular and spectral transmittance of the structure is modified from a Fano type to a pure Lorentzian line shape with a parallel and orthogonal polarizer-analyzer pair. This change leads to a linewidth narrowing that maximizes the sensor resolution, which we show to be of O(10−5) refractive index units (RIU). We estimate the potential of this system of O(10−6) RIU under optimal conditions.

A Variational Model for P+XS Image Fusion

Abstract: We propose an algorithm to increase the resolution of multispectral satellite images knowing the panchromatic image at high resolution and the spectral channels at lower resolution. Our algorithm is based on the assumption that, to a large extent, the geometry of the spectral channels is contained in the topographic map of its panchromatic image. This assumption, together with the relation of the panchromatic image to the spectral channels, and the expression of the low-resolution pixel in terms of the high-resolution pixels given by some convolution kernel followed by subsampling, constitute the elements for constructing an energy functional (with several variants) whose minima will give the reconstructed spectral images at higher resolution. We discuss the validity of the above approach and describe our numerical procedure. Finally, some experiments on a set of multispectral satellite images are displayed.

The 2D-S (Stereo) Probe: Design and Preliminary Tests of a New Airborne, High-Speed, High-Resolution Particle Imaging Probe

Abstract: The design, laboratory calibrations, and flight tests of a new optical imaging instrument, the twodimensional stereo (2D-S) probe, are presented. Two orthogonal laser beams cross in the middle of the sample volume. Custom, high-speed, 128-photodiode linear arrays and electronics produce shadowgraph images with true 10-m pixel resolution at aircraft speeds up to 250 m s 1 . An overlap region is defined by the two laser beams, improving the sample volume boundaries and sizing of small (100 m) particles, compared to conventional optical array probes. The stereo views of particles in the overlap region can also improve determination of three-dimensional properties of some particles. Data collected by three research aircraft are examined and discussed. The 2D-S sees fine details of ice crystals and small water drops coexisting in mixed-phase cloud. Measurements in warm cumuli collected by the NCAR C-130 during the Rain in Cumulus over the Ocean (RICO) project provide a test bed to compare the 2D-S with 2D cloud (2D-C) and 260X probes. The 2D-S sees thousands of cloud drops 150 m when the 2D-C and 260X probes see few or none. The data suggest that particle images and size distributions ranging from 25 to 150 m and collected at airspeeds 100 m s 1 by the 2D-C and 260X probes are probably (erroneously) generated from out-of-focus particles. Development of the 2D-S is in its infancy, and much work needs to be done to quantify its performance and generate software to analyze data.

Unsupervised, information-theoretic, adaptive image filtering for image restoration

Abstract: Image restoration is an important and widely studied problem in computer vision and image processing. Various image filtering strategies have been effective, but invariably make strong assumptions about the properties of the signal and/or degradation. Hence, these methods lack the generality to be easily applied to new applications or diverse image collections. This paper describes a novel unsupervised, information-theoretic, adaptive filter (UINTA) that improves the predictability of pixel intensities from their neighborhoods by decreasing their joint entropy. In this way, UINTA automatically discovers the statistical properties of the signal and can thereby restore a wide spectrum of images. The paper describes the formulation to minimize the joint entropy measure and presents several important practical considerations in estimating neighborhood statistics. It presents a series of results on both real and synthetic data along with comparisons with state-of-the-art techniques, including novel applications to medical image processing.

Recent developments in X-ray imaging with micrometer spatial resolution.

Abstract: X-ray detectors for imaging with a spatial resolution in the micrometer and submicrometer range have been developed at synchrotron radiation sources since 1996. The detectors consist of a scintillator, a light microscopy optic and a charge-coupled device (CCD). The scintillator converts part of the X-ray stopped by a material into a visible-light image which is projected onto the CCD by the light optics. A resolution of 0.5 microm FWHM has been achieved using a 1 microm-thick europium-doped Lu3Al5O12 film. The detective quantum efficiency of the detector is mainly limited by the low absorption of X-rays in the thin layer of the scintillator. To increase the absorption, and therefore reduce the exposure time, new scintillators (Lu2O3:Eu3+, Gd2O3:Eu3+, Lu2SiO5:Ce, Gd3Ga5O12:Eu3+, CdWO4) have been investigated. These were fabricated using sol-gel and liquid-phase epitaxy processes. Finally, the first fast microtomography experiment including radiation hardness of the optic is shown. This detector uses a high-intensity white beam with 60 keV effective energy and a fast CCD camera at up to 60 frames s(-1).

Performance Evaluation of the GE Healthcare eXplore VISTA Dual-Ring Small-Animal PET Scanner

Abstract: We evaluated the performance characteristics of the eXplore VISTA dual-ring small-animal PET scanner, a stationary, ring-type, depth-of-interaction (DOI) correcting system designed to simultaneously maximize sensitivity, resolution, and resolution uniformity over a field of view sufficient to image rodent-sized animals. Methods: We measured the intrinsic spatial resolution response of the VISTA detector modules, spatial and volume resolution throughout a representative portion of the field of view, and imaged several common resolution phantoms to provide a qualitative picture of resolution performance. We obtained an axial sensitivity profile and measured central point source sensitivity, scatter fractions and noise equivalent count (NEC) rates for rat- and mouse-sized objects using different energy windows, and count rate linearity. In addition, we measured the energy and timing resolution of both of the crystal layers (cerium-doped gadolinium orthosilicate and cerium-doped lutetium–yttrium orthosilicate) that give VISTA machines a DOI compensation capability. We examined the effectiveness of this DOI compensation by comparing spatial resolution measurements with and without the DOI correction enabled. Finally, several animal studies were included to illustrate system performance in the field. Results: Spatial and volume resolutions averaged approximately 1.4 mm and 2.9 mm3, respectively (with 3-dimensional Fourier rebinning and 2-dimensional filtered backprojection image reconstructions and an energy window of 250–700 keV), along the central axis of the scanner, and the spatial resolution was better than 1.7 mm and 2.1 mm at 1 and 2 cm off the central axis, respectively. Central point source sensitivity measured approximately 4% with peak NEC rates of 126.8 kcps at 455 kBq/mL and 77.1 kcps at 141 kBq/mL for mouse- and rat-sized uniform, cylindric phantoms, respectively. The radial spatial resolution at 2.8 cm off axis with DOI compensation was 2.5 mm but degraded (by 56%) to 3.9 mm without DOI compensation (as would be the case with a geometrically identical scanner without DOI correction capability). Conclusion: These results indicate that the VISTA small-animal PET scanner is well suited to imaging rodent-sized animals. The combination of high spatial resolution, resolution uniformity, sensitivity, and count rate performance, made possible in part by the novel use of phoswich detector modules, confers significant technical advantages over machines with similar geometry but without DOI correction capability.

High-resolution, real-time 3D absolute coordinate measurement based on a phase-shifting method

Abstract: We describe a high-resolution, real-time 3D absolute coordinate measurement system based on a phase-shifting method. It acquires 3D shape at 30 frames per second (fps), with 266K points per frame. A tiny marker is encoded in the projected fringe pattern, and detected by software from the texture image and the gamma map. Absolute 3D coordinates are obtained from the detected marker position and the calibrated system parameters. To demonstrate the performance of the system, we measure a hand moving over a depth distance of approximately 700 mm, and human faces with expressions. Applications of such a system include manufacturing, inspection, entertainment, security, medical imaging.

Distributed strain measurement with millimeter-order spatial resolution based on Brillouin optical correlation domain analysis

Abstract: Distributed strain sensing with millimeter-order spatial resolution is demonstrated in optical fibers based on Brillouin optical correlation domain analysis. A novel beat lock-in detection scheme is introduced to suppress background noises coming from the reflection of Brillouin pump waves. The Brillouin frequency shifts of 3 mm fiber sections are successfully measured with a theoretical spatial resolution of 1.6 mm.

Sub‐pixel mapping of rural land cover objects from fine spatial resolution satellite sensor imagery using super‐resolution pixel‐swapping

Abstract: Mapping rural land cover features, such as trees and hedgerows, for ecological applications is a desirable component of the creation of cartographic maps by the Ordnance Survey. Based on the phenomenon of spatial dependence, sub‐pixel mapping can provide increased mapping accuracy of such features. A simple pixel‐swapping algorithm for sub‐pixel mapping was applied to soft classified fine spatial resolution remotely sensed imagery. Initially, QuickbirdTM satellite sensor imagery with a spatial resolution of 2.6 m was acquired of the Christchurch area of Dorset, UK, and three field sites chosen. The imagery was soft classified using a supervised fuzzy c‐means algorithm and then super‐resolved into sub‐pixels using a zoom factor of five. Sub‐pixels within pixels were then iteratively swapped until the spatial correlation between sub‐pixels for the entire image was maximized. Mathematical morphology was used to suppress error in the super‐resolved output, increasing overall accuracy. Field data, including de...

Multispectral Image Analysis Using the Object-Oriented Paradigm

Abstract: Introduction Background Objects and Human Interpretation Process Object-Oriented Paradigm Organization of the Book Multispectral Remote Sensing Spatial Resolution Spectral Resolution Radiometric Resolution Temporal Resolution Multispectral Image Analysis Why an Object-Oriented Approach? Object Properties Advantages of Object-Oriented Approach Creating Objects Image Segmentation Techniques Creating and Classifying Objects at Multiple Scales Object Classification Creating Multiple Levels Creating Class Hierarchy and Classifying Objects Final Classification Using Object Relationships between Levels Object-Based Image Analysis Image Analysis Techniques Supervised Classification Using Multispectral Information Exploring the Spatial Dimension Using Contextual Information Taking Advantage of Morphology Parameters Taking Advantage of Texture Adding Temporal Dimension Advanced Object Image Analysis Techniques to Control Image Segmentation within eCognition Techniques to Control Image Segmentation within eCognition Multi-Scale Approach for Image Analysis Objects vs. Spatial Resolution Exploring the Parent-Child Object Relationships Using Semantic Relationships Taking Advantage of Ancillary Data Accuracy Assessment Sample Selection Sampling Techniques Ground Truth Collection Accuracy Assessment Measures References Index

Super-resolution in PET imaging

Abstract: This paper demonstrates a super-resolution method for improving the resolution in clinical positron emission tomography (PET) scanners. Super-resolution images were obtained by combining four data sets with spatial shifts between consecutive acquisitions and applying an iterative algorithm. Super-resolution attenuation corrected PET scans of a phantom were obtained using the two-dimensional and three-dimensional (3-D) acquisition modes of a clinical PET/computed tomography (CT) scanner (Discovery LS, GEMS). In a patient study, following a standard /sup 18/F-FDG PET/CT scan, a super-resolution scan around one small lesion was performed using axial shifts without increasing the patient radiation exposure. In the phantom study, smaller features (3 mm) could be resolved axially with the super-resolution method than without (6 mm). The super-resolution images had better resolution than the original images and provided higher contrast ratios in coronal images and in 3-D acquisition transaxial images. The coronal super-resolution images had superior resolution and contrast ratios compared to images reconstructed by merely interleaving the data to the proper axial location. In the patient study, super-resolution reconstructions displayed a more localized /sup 18/F-FDG uptake. A new approach for improving the resolution of PET images using a super-resolution method has been developed and experimentally confirmed, employing a clinical scanner. The improvement in axial resolution requires no changes in hardware.

Seamless image stitching by minimizing false edges

Abstract: Various applications such as mosaicing and object insertion require stitching of image parts. The stitching quality is measured visually by the similarity of the stitched image to each of the input images, and by the visibility of the seam between the stitched images. In order to define and get the best possible stitching, we introduce several formal cost functions for the evaluation of the stitching quality. In these cost functions the similarity to the input images and the visibility of the seam are defined in the gradient domain, minimizing the disturbing edges along the seam. A good image stitching will optimize these cost functions, overcoming both photometric inconsistencies and geometric misalignments between the stitched images. We study the cost functions and compare their performance for different scenarios both theoretically and practically. Our approach is demonstrated in various applications including generation of panoramic images, object blending and removal of compression artifacts. Comparisons with existing methods show the benefits of optimizing the measures in the gradient domain.

Hybrid retinal image registration

Abstract: This work studies retinal image registration in the context of the National Institutes of Health (NIH) Early Treatment Diabetic Retinopathy Study (ETDRS) standard. The ETDRS imaging protocol specifies seven fields of each retina and presents three major challenges for the image registration task. First, small overlaps between adjacent fields lead to inadequate landmark points for feature-based methods. Second, the non-uniform contrast/intensity distributions due to imperfect data acquisition will deteriorate the performance of area-based techniques. Third, high-resolution images contain large homogeneous nonvascular/texureless regions that weaken the capabilities of both feature-based and area-based techniques. In this work, we propose a hybrid retinal image registration approach for ETDRS images that effectively combines both area-based and feature-based methods. Four major steps are involved. First, the vascular tree is extracted by using an efficient local entropy-based thresholding technique. Next, zeroth-order translation is estimated by maximizing mutual information based on the binary image pair (area-based). Then image quality assessment regarding the ETDRS field definition is performed based on the translation model. If the image pair is accepted, higher-order transformations will be involved. Specifically, we use two types of features, landmark points and sampling points, for affine/quadratic model estimation. Three empirical conditions are derived experimentally to control the algorithm progress, so that we can achieve the lowest registration error and the highest success rate. Simulation results on 504 pairs of ETDRS images show the effectiveness and robustness of the proposed algorithm

Systems and methods for image resolution enhancement

Abstract: A system for providing enhanced digital images includes an image receiving device for accepting at least one digital image and obtaining digital information therefrom; a computer program product comprising machine readable instructions stored on machine readable media, the instructions for providing enhanced digital images by performing upon the at least one digital image at least one of: a minimum directional derivative search, a multi-channel median boosted anisotropic diffusion, an non-homogeneous anisotropic diffusion technique and a pixel compounding technique.