Showing papers on "Subpixel rendering published in 2004"

On the possibility of automatic multisensor image registration

Abstract: Multisensor image registration is needed in a large number of applications of remote sensing imagery. The accuracy achieved with usual methods (manual control points extraction, estimation of an analytical deformation model) is not satisfactory for many applications where a subpixel accuracy for each pixel of the image is needed (change detection or image fusion, for instance). Unfortunately, there are few works in the literature about the fine registration of multisensor images and even less about the extension of approaches similar to those based on fine correlation for the case of monomodal imagery. In this paper, we analyze the problem of the automatic multisensor image registration and we introduce similarity measures which can replace the correlation coefficient in a deformation map estimation scheme. We show an example where the deformation map between a radar image and an optical one is fully automatically estimated.

Novel subpixel layouts and arrangements for high brightness displays

Abstract: High brightness displays comprising subpixel repeating groups having at least white with a number of colored subpixels are disclosed. Colored subpixels may comprise: red, blue, green, cyan or magenta in these various embodiments.

Application of the stochastic mixing model to hyperspectral resolution enhancement

Abstract: A maximum a posteriori (MAP) estimation method is described for enhancing the spatial resolution of a hyperspectral image using a higher resolution coincident panchromatic image. The approach makes use of a stochastic mixing model (SMM) of the underlying spectral scene content to develop a cost function that simultaneously optimizes the estimated hyperspectral scene relative to the observed hyperspectral and panchromatic imagery, as well as the local statistics of the spectral mixing model. The incorporation of the stochastic mixing model is found to be the key ingredient for reconstructing subpixel spectral information in that it provides the necessary constraints that lead to a well-conditioned linear system of equations for the high-resolution hyperspectral image estimate. Here, the mathematical formulation of the proposed MAP method is described. Also, enhancement results using various hyperspectral image datasets are provided. In general, it is found that the MAP/SMM method is able to reconstruct subpixel information in several principal components of the high-resolution hyperspectral image estimate, while the enhancement for conventional methods, like those based on least squares estimation, is limited primarily to the first principal component (i.e., the intensity component).

Point matching under large image deformations and illumination changes

Abstract: To solve the general point correspondence problem in which the underlying transformation between image patches is represented by a homography, a solution based on extensive use of first order differential techniques is proposed. We integrate in a single robust M-estimation framework the traditional optical flow method and matching of local color distributions. These distributions are computed with spatially oriented kernels in the 5D joint spatial/color space. The estimation process is initiated at the third level of a Gaussian pyramid, uses only local information, and the illumination changes between the two images are also taken into account. Subpixel matching accuracy is achieved under large projective distortions significantly exceeding the performance of any of the two components alone. As an application, the correspondence algorithm is employed in oriented tracking of objects.

Subpixel rendering filters for high brightness subpixel layouts

Abstract: A display system comprises a display panel substantially comprising a subpixel repeating group tiled across the panel in a regular pattern. The subpixel repeating group comprises at least one white subpixel and a plurality of colored subpixels. The display system further comprises input circuitry configured to receive input image data indicating an image for rendering on the display panel, and subpixel rendering circuitry configured to compute an output luminance value for each subpixel of said display panel. The subpixel rendering circuitry multiplies data values of a spatial portion of the input image data by at least one image filter kernel which comprises a matrix of coefficients arranged such that each coefficient represents a fractional part of one of said data values of said spatial portion of said input image data. The subpixel rendering circuitry is further configured to sharpen the output luminance values using a luminance signal.

Generalized Distance Transforms and Skeletons in Graphics Hardware

Abstract: We present a framework for computing generalized distance transforms and skeletons of two-dimensional objects using graphics hardware. Our method is based on the concept of footprint splatting. Combining different splats produces weighted distance transforms for different metrics, as well as the corresponding skeletons and Voronoi diagrams. We present a hierarchical acceleration scheme and a subdivision scheme that allows visualizing the computed skeletons with subpixel accuracy in real time. Our splatting approach allows one to easily change all the metric parameters, treat any 2D boundaries, and easily produce both DTs and skeletons. We illustrate the method by several examples.

Registration and real-time visualization of transcranial magnetic stimulation with 3-D MR images

Abstract: This paper describes a method for registering and visualizing in real-time the results of transcranial magnetic stimulations (TMS) in physical space on the corresponding anatomical locations in MR images of the brain. The method proceeds in three main steps. First, the patient scalp is digitized in physical space with a magnetic-field digitizer, following a specific digitization pattern. Second, a registration process minimizes the mean square distance between those points and a segmented scalp surface extracted from the magnetic resonance image. Following this registration, the physician can follow the change in coil position in real-time through the visualization interface and adjust the coil position to the desired anatomical location. Third, amplitude of motor evoked potentials can be projected onto the segmented brain in order to create functional brain maps. The registration has subpixel accuracy in a study with simulated data, while we obtain a point to surface root-mean-square error of 1.17/spl plusmn/0.38 mm in a 24 subject study.

Full-color organic display having improved blue emission

Abstract: A full-color organic display for displaying a color image, including an array of pixels arranged in repeating patterns, wherein each pixel has red, green, and blue light-emitting subpixels, and wherein each red and green light-emitting subpixel contains only one EL unit, while each blue light-emitting subpixel contains more than one vertically stacked EL unit.

ART-MMAP: a neural network approach to subpixel classification

Abstract: Global or continental-scale land cover mapping with remote sensing data is limited by the spatial characteristics of satellites. Subpixel-level mapping is essential for the successful description of many land cover patterns with spatial resolution of less than /spl sim/1 km and also useful for finer resolution data. This paper presents a novel adaptive resonance theory MAP (ARTMAP) neural network-based mixture analysis model-ART mixture MAP (ART-MMAP). Compared to the ARTMAP model, ART-MMAP has an enhanced interpolation function that decreases the effect of category proliferation in ART/sub a/ and overcomes the limitation of class category in ART/sub b/. Results from experiments demonstrate the superiority of ART-MMAP in terms of estimating the fraction of land cover within a single pixel.

Image Data Set With Embedded Pre-Subpixel Rendered Image

Abstract: Various imaging processing techniques are disclosed for displaying a pre-subpixel rendered image. The pre-subpixel rendered image can be transmitted directly to a display capable of displaying a subpixel rendered image. The pre-subpixel rendered image can also be stored for later transmission for output to the display. Additionally, the pre-subpixel rendered image can be embedded in an image data stream and later extracted and displayed. Furthermore, various techniques have been disclosed to embed and extract the pre-subpixel rendered image.

System and method for performing image reconstruction and subpixel rendering to effect scaling for multi-mode display

Abstract: An image processing system that receives source image data with a first resolution and renders a target image data onto a display having a second subpixel resolution and improves image quality in said rendered target image data is described.

Fast motion estimation using bidirectional gradient methods

Abstract: Gradient-based motion estimation methods (GMs) are considered to be in the heart of state-of-the-art registration algorithms, being able to account for both pixel and subpixel registration and to handle various motion models (translation, rotation, affine, and projective). These methods estimate the motion between two images based on the local changes in the image intensities while assuming image smoothness. This paper offers two main contributions. The first is enhancement of the GM technique by introducing two new bidirectional formulations of the GM. These improve the convergence properties for large motions. The second is that we present an analytical convergence analysis of the GM and its properties. Experimental results demonstrate the applicability of these algorithms to real images.

Hardware based interdigitation

Abstract: A system and method for interdigitating multiple perspective views in a stereoscopic image viewing system. A lenticular sheet is affixed in intimate juxtaposition with a display area having a defined aspect ratio. The display area includes a plurality of scan lines each having a plurality of pixels, each pixel including subpixels. A map having the same resolution as the display is created to store values corresponding to each subpixel in the display area. Preferably, the map is generated beforehand and stored for later use through a lookup operation. A buffer stores a frame having n views, wherein each of the n views has the same aspect ratio as the display area. A plurality of masks is also created and stored. Each mask corresponds to a unique one of the n views and includes opaque areas and a plurality of transparent windows, each of which corresponds to a selected subpixel location. The n views are then interdigitated while applying the corresponding masks, and a value is assigned to each subpixel using the map.

Estimation of subpixel target size for remotely sensed imagery

Abstract: One of the challenges in remote sensing image processing is subpixel detection where the target size is smaller than the ground sampling distance, therefore, embedded in a single pixel. Under such a circumstance, these targets can be only detected spectrally at the subpixel level, not spatially as ordinarily conducted by classical image processing techniques. This paper investigates a more challenging issue than subpixel detection, which is the estimation of target size at the subpixel level. More specifically, when a subpixel target is detected, we would like to know "what is the size of this particular target within the pixel?". The proposed approach is to estimate the abundance fraction of a subpixel target present in a pixel, then find what portion it contributes to the pixel that can be used to determine the size of the subpixel target by multiplying the ground sampling distance. In order to make our idea work, the subpixel target abundance fraction must be accurately estimated to truly reflect the portion of a subpixel target occupied within a pixel. So, a fully constrained linear unmixing method is required to reliably estimate the abundance fractions of a subpixel target for its size estimation. In this paper, a recently developed fully constrained least squares linear unmixing is used for this purpose. Experiments are conducted to demonstrate the utility of the proposed method in comparison with an unconstrained linear unmixing method, unconstrained least squares method, two partially constrained least square linear unmixing methods, sum-to-one constrained least squares, and nonnegativity constrained least squares.

Georegistration of Landsat data via robust matching of multiresolution features

Abstract: The goal of the project described in this paper is to build a prototype of an operational system, which will provide registration within subpixel accuracy of multitemporal Landsat data, acquired by either Landsat-5 or Landsat-7 Thematic Mapper instruments. Integrated within an automated mass processing system for Landsat data, the input to our registration system consists of scenes that have been geometrically and radiometrically corrected, as well as preprocessed for detection of clouds and cloud shadows. Such preprocessed scenes are then georegistered relative to a database of Landsat chips. This paper describes the entire registration process, including the use of landmark chips, feature extraction performed by an overcomplete wavelet representation, and feature matching using statistically robust techniques. Knowing the approximate longitudes and latitudes or the UTM coordinates of the four corners of each incoming scene, a subset of the chips that represent landmarks included in the scene are selected to perform the registration. For each of these selected landmark chips, a corresponding window is extracted from the incoming scene, and each chip-window pair is registered using a robust wavelet feature-matching methodology. Based on the transformations from the chip-window pairs, a global transformation is then computed for the entire scene using a variant of a robust least median of squares estimator. Empirical results of this registration process, which provided subpixel accuracy for several multitemporal scenes from different study areas, are presented and discussed.

Apparatus and Method of Converting Image Signal for Six Color Display Device, and Six Color Display Device Having Optimum Subpixel Arrangement

Abstract: A method of converting image signals for a display device including six-color subpixels is provided, which includes: classifying three-color input image signals into maximum, middle, and minimum; decomposing the classified signals into six-color components; determining a maximum among the six-color components; calculating a scaling factor; and extracting six-color output signals.

Super-Resolution Land Cover Classification Using the Two-Point Histogram

Abstract: A geostatistical optimization algorithm is proposed for super-resolution land cover classification from remotely sensed imagery. The algorithm requires as input, a soft classification of land cover obtained from a remotely sensed image. A super-resolution (sub-pixel scale) grid is defined. The soft land cover proportions (pixel scale) are then transformed into a hard classification (subpixel scale) by allocating hard classes randomly to the sub-pixels. The number allocated per pixel is determined in proportion to the original land cover proportion per pixel. The algorithm optimizes the match between a target and current realization of the two-point histogram by swapping sub-pixel classes within pixels such that the original class proportions defined per pixel are maintained. The algorithm is demonstrated for two simple simulated images. The advantages of the approach are its ability to recreate any target spatial distribution and to work with features that are both large and small relative to the pixel size, in combination.

Noise in flat-panel displays with subpixel structure.

Abstract: Subpixel structures found in medical monochrome active-matrix liquid crystal displays (AMLCDs) affect noise estimates measured with conventional methods. In this work, we discuss methods that identify sources of noise and permit the comparison of luminance noise estimates across technologies independent of pixel design and device technology. We used a three-million pixel AMLCD with a pixel structure consisting of three color stripes, each in a two-domain, in-plane switching mode. Images of uniform fields displayed on the AMLCD were acquired using a low-noise, high-resolution CCD camera. The camera noise and flat-field response were characterized using a uniform light source constructed for this purpose. We show results in terms of spatial luminance noise and noise power spectrum for high-resolution images and for the same images processed with a pixel-aligned aperture. We find that the pixel-aligned aperture eliminates almost all the noise found in the high-resolution images, suggesting that most of the luminance noise in AMLCDs comes from the subpixel structure and less-than-100% aperture ratio, rather than from interpixel variations.

AAPM/RSNA tutorial on equipment selection: PACS equipment overview display systems

Abstract: Display systems are key components of the digital radiology department. Current display systems for medical imaging are based on cathode-ray tubes (CRTs) or active-matrix liquid crystal displays (AMLCDs). The CRT is a cathodoluminescent display: Light is generated by exciting a luminescent material with energetic electrons. AMLCDs are light-modulating devices that form the image in the screen by controlling the transparency of individual display pixels. Many image quality aspects of CRTs are determined by the way the pixel luminance is generated in the cathodoluminescent screen. The resolution properties of AMLCDs are much better than those of CRTs. In CRT devices, phosphor granularity and raster scanning patterns are the main components of spatial noise. In AMLCDs, the most notable feature of the noise characteristic is the subpixel structure of complex pixel designs used in medical displays. The small-spot contrast of CRTs is dominated mainly by veiling glare and reflections of ambient illumination. In addition to display reflectance, the contrast of medical AMLCDs is affected by crosstalk and by variations of the luminance at off-normal viewing angles.

Influence of thresholding on centroid statistics: full analytical description

Abstract: The centroid method is a common procedure for subpixel location that is applied to a large number of optical sensors. In practice, it is always accompanied by thresholding algorithms used to eliminate undesirable background that may decrease precision. We present a full analytical description of the interaction between centroiding and thresholding applied over an intensity distribution corrupted by additive Gaussian noise. An in depth analysis of the most outstanding statistical properties of this relation (mean and variance) is also presented by means of simulated and experimental data. This work provides fundamental concepts to the designers of sensors that are based on centroid measurements to allow them to use thresholding correctly before centroid computation.

Enhancing registration tolerance of extended visual cryptography for natural images

Abstract: Extended visual cryptography [Ateniese et al., Theor. Comput. Sci. 250, 143–161 (2001)] is a method that encodes a number of images so that when the images are superimposed, a hidden image appears while the original images disappear. The decryption is done directly by human eyes without cryptographic calculations. Our proposed system takes three natural images as input and generates two images that are modifications of two of the input pictures. The third picture is viewed by superimposing the two output images. A trade-off exists between the number of gray levels and the difficulty in stacking the two sheets. Our new approach enhances the registration tolerance to obtain the third image and reduces the difficulty of superimposing the image while allowing a variety of gray levels. It is done by extending dot-clustered subpixel arrangements and enabling continuous gray-scale subpixel values. The system has considerably enhanced tolerance to the registration error. We show this by superimposing the output by computer simulation and calculating the peak SNRs with the original images.

Robust phase correlation

Abstract: Phase-correlation (PC) is a computationally efficient method for two and three dimensional translation estimation. We present a projection operator, which significantly improves the accuracy and robustness of the PC scheme. The operator projects the estimated correlation function into the space of correlation functions resulting from a certain range of translations, while rejecting components which are unrelated to the estimated motion. Thus, the registration accuracy is improved by an order of magnitude, especially in the registration of noisy images and volumes. In addition, this approach is shown to be complementary with other subpixel phase correlation based techniques.

Point target detection and subpixel position estimation in optical imagery

Abstract: We address the issue of distinguishing point objects from a cluttered background and estimating their position by image processing. We are interested in the specific context in which the object's signature varies significantly relative to its random subpixel location because of aliasing. The conventional matched filter neglects this phenomenon and causes a consistent degradation of detection performance. Thus alternative detectors are proposed, and numerical results show the improvement brought by approximate and generalized likelihood-ratio tests compared with pixel-matched filtering. We also study the performance of two types of subpixel position estimator. Finally, we put forward the major influence of sensor design on both estimation and point object detection.

A hybrid algorithm for subpixel detection in hyperspectral imagery

Abstract: Numerous subpixel detection algorithms utilizing structured backgrounds have been developed over the past few years. These range from detection schemes based on spectral unmixing to generalized likelihood ratio tests. Spectral unmixing algorithms such as the Fully Constrained Least Squares (FCLS) algorithm have the advantage of physically modeling the interactions of spectral signatures based on reflectance/emittance spectroscopy. Generalized likelihood ratio tests like the Adaptive Matched Subspace Detector (AMSD) have the advantage of identifying targets that are statistically different from the background. Therefore, a hybrid detector based on both AMSD and FCLS was developed to take advantage of each detector's strengths. Results demonstrate that the hybrid detector achieved the lowest false alarm rates while also producing meaningful abundance estimates

Image degradation correction in novel liquid crystal displays with split blue subpixels

Abstract: Systems and methods are disclosed to correct for image degraded signals on a liquid crystal display panel are disclosed. Panels that comprise a subpixel repeating group having an even number of subpixels in a first direction may have parasitic capacitance and other signal errors due to imperfect dot inversion schemes thereon. Techniques for signal correction and localizing of errors onto particular subpixels are disclosed.

Simplex projection methods for selection of endmembers in hyperspectral imagery

Abstract: It is well known that performance of subpixel target detection algorithms depends on the choice of endmembers used to characterize the background and the target in hyperspectral imagery. In this paper, we investigate how well a set of endmembers characterizes a given set of spectra. We are assuming a fully constrained linear mixing model, and analyze the resulting residuals. To facilitate geometric and intuitive interpretation, we formulate the resulting constrained least-squares estimation problem in terms of projections on low-dimensional simplexes. Consequently, we define a family of simplex projection methods (SPM) for endmember selection. We give numerical results for two known endmember-selection procedures -the pixel purity index (PPI) and the maximum distance (MaxD) methods. Then we compare these results to those for a simple version of SMP, called the Farthest Pixel Selection (FPS) method. This new class of techniques promises to give better descriptions of the target and background regions than do current methods, which in turn should lead to more precise detection (with lower false alarm rates) of low-visibility small (subpixel) targets

A SPLIT Model for Extraction of Subpixel Impervious Surface Information

Abstract: This paper introduces a Subpixel Proportional Land cover Information Transformation (SPLIT) model to extract proportions of impervious surfaces in urban and suburban areas. High spatial resolution airborne Digital Multispectral Videography (DMSV) data provided subpixel information for Landsat TM data. The SPLIT model employed a Modularized Artificial Neural Network (MANN) to integrate multi-sensor remote sensing data and to extract proportions of impervious surfaces and other types of land cover within TM pixels. Through a control unit, the MANN was able to decompose a complex task into multiple subtasks by using a group of sub-networks. The SPLIT model identified spectral relations between TM pixel values and the corresponding DMSV subpixel patterns. The established relationship allows extrapolation of the SPLIT model to the areas beyond DMSV data coverage. We applied five intervals, i.e., 81 percent, to map the subpixel proportions of land cover types. We extrapolated the SPLIT model from training sites that have both TM and DMSV coverage into the entire DuPage County with TM data as the input. The extrapolation received 82.9 percent overall accuracy for the extracted proportions of urban impervious surface.

Cross-sensor calibration between Ikonos and Landsat ETM+ for spectral mixture analysis

Abstract: Spectral mixture analysis is an algorithm that is developed to overcome the weakness in traditional land-use/land-cover (LULC) classification where each picture element (pixel) from remote sensing is assigned to one and only one LULC type. In reality, a remotely sensed signal from a pixel is often a spectral mixture from several LULC types. Spectral mixture analysis can derive subpixel proportions for the endmembers from remotely sensed data. However, one frequently faces the problem in determining the spectral signatures for the endmembers. This study provides a cross-sensor calibration algorithm that enables us to obtain the endmember signatures from an Ikonos multispectral image for spectral mixture analysis using Landsat ETM+ images. The calibration algorithm first converts the raw digital numbers from both sensors into at-satellite reflectance. Then, the Ikonos at-satellite reflectance image is degraded to match the spatial resolution of the Landsat ETM+ image. The histograms at the same spatial resolution from the two images are matched, and the signatures from the pure pixels in the Ikonos image are used as the endmember signatures. Validation of the spectral mixture analysis indicates that the simple algorithm works effectively. The algorithm is not limited to Ikonos and Landsat sensors. It is, in general, applicable to spectral mixture analysis where a high spatial resolution sensor and a low spatial resolution sensor with similar spectral resolutions are available as long as images collected by the two sensors are close in time over the same place.