Showing papers on "Pixel published in 2002"

Example-based super-resolution

Abstract: We call methods for achieving high-resolution enlargements of pixel-based images super-resolution algorithms. Many applications in graphics or image processing could benefit from such resolution independence, including image-based rendering (IBR), texture mapping, enlarging consumer photographs, and converting NTSC video content to high-definition television. We built on another training-based super-resolution algorithm and developed a faster and simpler algorithm for one-pass super-resolution. Our algorithm requires only a nearest-neighbor search in the training set for a vector derived from each patch of local image data. This one-pass super-resolution algorithm is a step toward achieving resolution independence in image-based representations. We don't expect perfect resolution independence-even the polygon representation doesn't have that-but increasing the resolution independence of pixel-based representations is an important task for IBR.

Fast bilateral filtering for the display of high-dynamic-range images

Abstract: We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. Only the base layer has its contrast reduced, thereby preserving detail. The base layer is obtained using an edge-preserving filter called the bilateral filter. This is a non-linear filter, where the weight of each pixel is computed using a Gaussian in the spatial domain multiplied by an influence function in the intensity domain that decreases the weight of pixels with large intensity differences. We express bilateral filtering in the framework of robust statistics and show how it relates to anisotropic diffusion. We then accelerate bilateral filtering by using a piecewise-linear approximation in the intensity domain and appropriate subsampling. This results in a speed-up of two orders of magnitude. The method is fast and requires no parameter setting.

Detection algorithms for hyperspectral imaging applications

Abstract: We introduce key concepts and issues including the effects of atmospheric propagation upon the data, spectral variability, mixed pixels, and the distinction between classification and detection algorithms. Detection algorithms for full pixel targets are developed using the likelihood ratio approach. Subpixel target detection, which is more challenging due to background interference, is pursued using both statistical and subspace models for the description of spectral variability. Finally, we provide some results which illustrate the performance of some detection algorithms using real hyperspectral imaging (HSI) data. Furthermore, we illustrate the potential deviation of HSI data from normality and point to some distributions that may serve in the development of algorithms with better or more robust performance. We therefore focus on detection algorithms that assume multivariate normal distribution models for HSI data.

Hyperspectral image data analysis

Abstract: The fundamental basis for space-based remote sensing is that information is potentially available from the electromagnetic energy field arising from the Earth's surface and, in particular, from the spatial, spectral, and temporal variations in that field. Rather than focusing on the spatial variations, which imagery perhaps best conveys, why not move on to look at how the spectral variations might be used. The idea was to enlarge the size of a pixel until it includes an area that is characteristic from a spectral response standpoint for the surface cover to be discriminated. The article includes an example of an image space representation, using three bands to simulate a color IR photograph of an airborne hyperspectral data set over the Washington, DC, mall.

Drizzle: A Method for the Linear Reconstruction of Undersampled Images

Abstract: We have developed a method for the linear reconstruction of an image from undersampled, dithered data. The algorithm, known as Variable-Pixel Linear Reconstruction, or informally as “Drizzle”, preserves photometry and resolution, can weight input images according to the statistical significance of each pixel, and removes the effects of geometric distortion both on image shape and photometry. This paper presents the method and its implementation. The photometric and astrometric accuracy and image fidelity of the algorithm as well as the noise characteristics of output images are discussed. In addition, we describe the use of drizzling to combine dithered images in the presence of cosmic rays.

A Wavelet-Based Algorithm for the Spatial Analysis of Poisson Data

Abstract: Wavelets are scalable, oscillatory functions that deviate from zero only within a limited spatial regime and have average value zero, and thus may be used to simultaneously characterize the shape, location, and strength of astronomical sources. But in addition to their use as source characterizers, wavelet functions are rapidly gaining currency within the source detection field. Wavelet-based source detection involves the correlation of scaled wavelet functions with binned, two-dimensional image data. If the chosen wavelet function exhibits the property of vanishing moments, significantly nonzero correlation coefficients will be observed only where there are high-order variations in the data; e.g., they will be observed in the vicinity of sources. Source pixels are identified by comparing each correlation coefficient with its probability sampling distribution, which is a function of the (estimated or a priori known) background amplitude. In this paper, we describe the mission-independent, wavelet-based source detection algorithm "WAVDETECT," part of the freely available Chandra Interactive Analysis of Observations (CIAO) software package. Our algorithm uses the Marr, or "Mexican Hat" wavelet function, but may be adapted for use with other wavelet functions. Aspects of our algorithm include: (1) the computation of local, exposure-corrected normalized (i.e., flat-fielded) background maps; (2) the correction for exposure variations within the field of view (due to, e.g., telescope support ribs or the edge of the field); (3) its applicability within the low-counts regime, as it does not require a minimum number of background counts per pixel for the accurate computation of source detection thresholds; (4) the generation of a source list in a manner that does not depend upon a detailed knowledge of the point spread function (PSF) shape; and (5) error analysis. These features make our algorithm considerably more general than previous methods developed for the analysis of X-ray image data, especially in the low count regime. We demonstrate the robustness of WAVDETECT by applying it to an image from an idealized detector with a spatially invariant Gaussian PSF and an exposure map similar to that of the Einstein IPC; to Pleiades Cluster data collected by the ROSAT PSPC; and to simulated Chandra ACIS-I image of the Lockman Hole region.

Rapid shape acquisition using color structured light and multi-pass dynamic programming

Abstract: This paper presents a color structured light technique for recovering object shape from one or more images. The technique works by projecting a pattern of stripes of alternating colors and matching the projected color transitions with observed edges in the image. The correspondence problem is solved using a novel, multi-pass dynamic programming algorithm that eliminates global smoothness assumptions and strict ordering constraints present in previous formulations. The resulting approach is suitable for generating both high-speed scans of moving objects when projecting a single stripe pattern and high-resolution scans of static scenes using a short sequence of time-shifted stripe patterns. In the latter case, space-time analysis is used at each sensor pixel to obtain inter-frame depth localization. Results are demonstrated for a variety of complex scenes.

Spatial/spectral endmember extraction by multidimensional morphological operations

Abstract: Spectral mixture analysis provides an efficient mechanism for the interpretation and classification of remotely sensed multidimensional imagery. It aims to identify a set of reference signatures (also known as endmembers) that can be used to model the reflectance spectrum at each pixel of the original image. Thus, the modeling is carried out as a linear combination of a finite number of ground components. Although spectral mixture models have proved to be appropriate for the purpose of large hyperspectral dataset subpixel analysis, few methods are available in the literature for the extraction of appropriate endmembers in spectral unmixing. Most approaches have been designed from a spectroscopic viewpoint and, thus, tend to neglect the existing spatial correlation between pixels. This paper presents a new automated method that performs unsupervised pixel purity determination and endmember extraction from multidimensional datasets; this is achieved by using both spatial and spectral information in a combined manner. The method is based on mathematical morphology, a classic image processing technique that can be applied to the spectral domain while being able to keep its spatial characteristics. The proposed methodology is evaluated through a specifically designed framework that uses both simulated and real hyperspectral data.

Segmentation and histogram generation using the HSV color space for image retrieval

Abstract: We have analyzed the properties of the HSV (hue, saturation and value) color space with emphasis on the visual perception of the variation in hue, saturation and intensity values of an image pixel. We extract pixel features by either choosing the hue or the intensity as the dominant property based on the saturation value of a pixel. The feature extraction method has been applied for both image segmentation as well as histogram generation applications - two distinct approaches to content based image retrieval (CBIR). Segmentation using this method shows better identification of objects in an image. The histogram retains a uniform color transition that enables us to do a window-based smoothing during retrieval. The results have been compared with those generated using the RGB color space.

A hierarchical approach to robust background subtraction using color and gradient information

Abstract: We present a background subtraction method that uses multiple cues to detect objects robustly in adverse conditions. The algorithm consists of three distinct levels, i.e., pixel level, region level and frame level. At the pixel level, statistical models of gradients and color are separately used to classify each pixel as belonging to background or foreground. In the region level, foreground pixels obtained from the color based subtraction are grouped into regions and gradient based subtraction is then used to make inferences about the validity of these regions. Pixel based models are updated based on decisions made at the region level. Finally, frame level analysis is performed to detect global illumination changes. Our method provides the solution to some of the common problems that are not addressed by most background subtraction algorithms, such as fast illumination changes, repositioning of static background objects, and initialization of background model with moving objects present in the scene.

High dynamic range display devices

Abstract: A display has a first array of pixels connected to emit individually-controlled amounts of light onto a second array of pixels. The second array of pixels is connected to pass individually-controllable portions of the light. The display has a controller connected to control the pixels of the first and second arrays of pixels. The controller is configured to control the pixels of the first array of pixels to provide on the second array of pixels an approximation of an image specified by image data; determine a difference between the image and the approximation of the image at individual pixels of the second array of pixels; and control the pixels of the second array of pixels to modulate the approximation of the image according to the corresponding determined differences.

Integral three-dimensional imaging with digital reconstruction

Abstract: A computer-based three-dimensional image reconstruction method and system are presented. An elemental image array of a three-dimensional object is formed by a micro-lens array, and recorded by a CCD camera. Three-dimensional images are reconstructed by extracting pixels periodically from the elemental image array using a computer. Images viewed from an arbitrary angle can be retrieved by shifting which pixels are to be extracted. Image processing methods can be used to enhance the reconstructed image. Further, the digitally reconstructed images can be sent via a network. A system for imaging a three-dimensional object includes a micro-lens array that generates an elemental image array. The elemental image array is detected by a CCD camera to generate digitized image information. A computer processes the digitized image information to reconstruct an image of the three-dimensional object. A two-dimensional display device may be connected directly or indirectly to the computer to display the image of the three-dimensional object. The computer may also be used to generate virtual image information of a virtual three-dimensional object. This can then be combined with the digitized image information to provide combined image information. The two-dimensional display device may be used to display a virtual image or a combined image.

Methods, systems, and programming for computer display of images, text, and/or digital content

Abstract: A bitmap of a shape, such as a font, can be subpixel optimized by producing for each of a display's subpixels a coverage value representing the percent of its area covered by the shape being represented and by distributing, to prevent color imbalance, an amount of a given subpixel's coverage value to nearby subpixels of different colors as a function of the percent of the given subpixel's coverage value that causes color imbalance. Web pages can be displayed with scaled-down and subpixel optimized images. A given layout of a Web page can be displayed at each of at least two different selected scale factors, with the font bitmaps used to represent characters in the display at each scale factor having their shape and pixel alignment selected to improve readability for the particular pixel size at which they are displayed at each such scale factor.

A compact and efficient image retrieval approach based on border/interior pixel classification

Abstract: This paper presents \bic (Border/Interior pixel Classification), a compact and efficient CBIR approach suitable for broad image domains It has three main components: (1) a simple and powerful image analysis algorithm that classifies image pixels as either border or interior, (2) a new logarithmic distance (dLog) for comparing histograms, and (3) a compact representation for the visual features extracted from images Experimental results show that the BIC approach is consistently more compact, more efficient and more effective than state-of-the-art CBIR approaches based on sophisticated image analysis algorithms and complex distance functions It was also observed that the dLog distance function has two main advantages over vectorial distances (eg, L1): (1) it is able to increase substantially the effectiveness of (several) histogram-based CBIR approaches and, at the same time, (2) it reduces by 50% the space requirement to represent a histogram

A feature-based, robust, hierarchical algorithm for registering pairs of images of the curved human retina

Abstract: This paper describes a robust hierarchical algorithm for fully-automatic registration of a pair of images of the curved human retina photographed by a fundus microscope. Accurate registration is essential for mosaic synthesis, change detection, and design of computer-aided instrumentation. Central to the algorithm is a 12-parameter interimage transformation derived by modeling the retina as a rigid quadratic surface with unknown parameters. The parameters are estimated by matching vascular landmarks by recursively tracing the blood vessel structure. The parameter estimation technique, which could be generalized to other applications, is a hierarchy of models and methods, making the algorithm robust to unmatchable image features and mismatches between features caused by large interframe motions. Experiments involving 3,000 image pairs from 16 different healthy eyes were performed. Final registration errors less than a pixel are routinely achieved. The speed, accuracy, and ability to handle small overlaps compare favorably with retinal image registration techniques published in the literature.

Image processing system to control vehicle headlamps or other vehicle equipment

Abstract: An imaging system (fig.1) includes an image array sensor (101) including a plurality of pixels (102). Each pixel (102) generates a signal indicative of the amount of light received on the pixel. The imaging system further includes an analog to digital converter (103) for converting the signals from the pixels into a digital value. The system further includes a memory (106) including a plurality of allocated storage locations for storing the digital values from the converter. The number of allocated storage locations in the memory is less than the number of pixels in the image array sensor.

Optical reader having partial frame operating mode

Abstract: The invention is an optical reader having a 2D image sensor that is configured to operate in a partial frame capture mode. In a partial frame operating mode, the reader clocks out and captures at least one partial frame of image data having image data corresponding to less than all of the pixels of an image sensor pixel array. In one embodiment, the reader operating in a partial frame operating mode captures image data corresponding to a linear pattern of pixels of the image sensor, reads the image data, attempts to decode for a decodable 1D symbol which may be represented in the image data, and captures a full frame of image data if the image data reading reveals a 2D symbol is likely to be present in a full field of view of the 2D image sensor.

Multispectral color image capture using a liquid crystal tunable filter

Abstract: We describe the experimental setup of a multispectral color image acquisition system consisting of a professional monochrome CCD camera and a tunable filter in which the spectral transmittance can be controlled electronically. We perform a spectral characterization of the acquisition system taking into account the acquisition noise. To convert the camera output signals to device-independent color data, two main approaches are proposed and evaluated. One consists in applying regression methods to convert from the K camera outputs to a device-independent color space such as CIEXYZ or CIELAB. Another method is based on a spectral model of the acquisition system. By inverting the model using a principal eigenvector approach, we estimate the spectral reflectance of each pixel of the imaged surface.

Color texture moments for content-based image retrieval

Abstract: We adopt a local Fourier transform as a texture representation scheme and derive eight characteristic maps for describing different aspects of cooccurrence relations of image pixels in each channel of the (SVcosH, SVsinH, V) color space. Then we calculate the first and second moments of these maps as a representation of the natural color image pixel distribution, resulting in a 48-dimensional feature vector. The novel low-level feature is named color texture moments (CTM), which can also be regarded as a certain extension to color moments in eight aspects through eight orthogonal templates. Experiments show that this new feature can achieve good retrieval performance for CBIR.

Hyperplane approximation for template matching

Abstract: Hager and Belhumeur (1998) proposed a general framework for object tracking in video images. It consists of low-order parametric models for the image motion of a target region. These models are used to predict movement and to track the target. The difference in intensity between the pixels belonging to the current region and the pixels of the selected target (learned during an offline stage) allows a straightforward prediction of the region position in the current image. The main aim of the article is to propose an important improvement within this framework, making the convergence faster with the same amount of online computation.

Representations of world coordinates in FITS

Abstract: The initial descriptions of the FITS format provided a simplified method for describing the physical coordinate values of the image pixels, but deliberately did not specify any of the detailed conventions required to convey the complexities of actual image coordinates. Building on conventions in wide use within astronomy, this paper proposes general extensions to the original methods for describing the world coordinates of FITS data. In subsequent papers, we apply these general conventions to the methods by which spherical coordinates may be projected onto a two-dimensional plane and to frequency/wavelength/velocity coordinates.

Vision-based operating method and system

Abstract: A vision-based operating system is provided in which a computer-based system accepts visual inputs and takes appropriate actions in a wide variety of environments. One environment is a security environment in which the vision-based operating system acquires an image of a face and determines, with an arbitrarily small probability of a false positive, whether the face is of a person who is authorized to enter the environment. The method employed may include acquiring a digital image for comparison to a reference image and identifying a group of pixels in the acquired image. A pixel group in the reference image that is the best match for the pixel group in the acquired image is selected. These steps are repeated for at least one more group of pixels. The relative locations of the selected pixel groups in the reference images and the pixel groups in the acquired image are compared, and the probability that the relative locations occurred randomly is determined.

Data hiding watermarking for halftone images

Abstract: In many printer and publishing applications, it is desirable to embed data in halftone images. We proposed some novel data hiding methods for halftone images. For the situation in which only the halftone image is available, we propose data hiding smart pair toggling (DHSPT) to hide data by forced complementary toggling at pseudo-random locations within a halftone image. The complementary pixels are chosen to minimize the chance of forming visually undesirable clusters. Our experimental results suggest that DHSPT can hide a large amount of hidden data while maintaining good visual quality. For the situation in which the original multitone image is available and the halftoning method is error diffusion, we propose the modified data hiding error diffusion (MDHED) that integrates the data hiding operation into the error diffusion process. In MDHED, the error due to the data hiding is diffused effectively to both past and future pixels. Our experimental results suggest that MDHED can give better visual quality than DHSPT. Both DHSPT and MDHED are computationally inexpensive.

Light emitting device and electronic apparatus using the same

Abstract: Providing a light emitting device capable of suppressing the variations of luminance of OLEDs associated with the deterioration of an organic light emitting material, and achieving a consistent luminance. An input video signal is constantly or periodically sampled to sense a light emission period or displayed gradation level of each of light emitting elements of pixels and then, a pixel suffering the greatest deterioration and decreased luminance is predicted from the accumulations of the sensed values. A voltage supply to the target pixel is corrected for achieving a desired luminance. The other pixels than the target pixel are supplied with an excessive voltage and hence, the individual gradation levels of the pixels are lowered by correcting the video signal for driving the pixel with the deteriorated light emitting element on as-needed basis, the correction of the video signal made by comparing the accumulation of the sensed values of each of the other pixels with a previously stored data on a time-varying luminance characteristic of the light emitting element.

Segmented layered image system

Abstract: Systems and methods for encoding and decoding document images are disclosed. Document images are segmented into multiple layers according to a mask. The multiple layers are non-binary. The respective layers can then be processed and compressed separately in order to achieve better compression of the document image overall. A mask is generated from a document image. The mask is generated so as to reduce an estimate of compression for the combined size of the mask and multiple layers of the document image. The mask is then employed to segment the document image into the multiple layers. The mask determines or allocates pixels of the document image into respective layers. The mask and the multiple layers are processed and encoded separately so as to improve compression of the document image overall and to improve the speed of so doing. The multiple layers are non-binary images and can, for example, comprise a foreground image and a background image.