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Geometric transformations for video compression and human teleoperator display

A method for bandwidth-efficient processing of video imagery to be viewed by the teleoperator of a remotely-operated vehicle on which the camera is mounted is described. The method comprises image coding, transmission, and reconstruction. It is assumed that the transmission bandpass is the limiting factor rather than encoding/decoding schemata; that image coding and reconstruction will be done within the general abilities of the NASA/TI Programmable Remapper; and that the ratio of retained local detail to the operator's visual resolution is held constant throughout the large-field image that is seen. Novel features include that the compression and reconstruction address certain characteristics of the human visual system, that two-way communication controls a moving 'fovea' in the transformation, and that resolution varies over the image. Conventional motivations accommodated include the Cartesian raster-scan nature of available imagers and display devices and a need for low bandwidth in the image transmission. Unique image processing hardware, NASA's Programmable Remapper, allows demonstration of the method. Once refined, the technology could be adapted to special purpose imagers and display devices, or otherwise to dedicated image processing hardware.

Juday, Richard D.

Coding isotropic images

Rate distortion functions for two-dimensional homogeneous isotropic images are compared with the performance of 5 source encoders designed for such images. Both unweighted and frequency weighted mean square error distortion measures are considered. The coders considered are differential PCM (DPCM) using six previous samples in the prediction, herein called 6 pel (picutre element) DPCM; simple DPCM using single sample prediction; 6 pel DPCM followed by entropy coding; 8 x 8 discrete cosine transform coder, and 4 x 4 Hadamard transform coder. Other transform coders were studied and found to have about the same performance as the two transform coders above. With the mean square error distortion measure DPCM with entropy coding performed best. The relative performance of the coders changes slightly when the distortion measure is frequency weighted mean square error. The performance of all the coders was separated by only about 4 dB.

Oneal, J. B., Jr.

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

Huck, Friedrich O.

Reconstruction of coded aperture images

Balanced correlation method and the Maximum Entropy Method (MEM) were implemented to reconstruct a laboratory X-ray source as imaged by a Uniformly Redundant Array (URA) system. Although the MEM method has advantages over the balanced correlation method, it is computationally time consuming because of the iterative nature of its solution. Massively Parallel Processing, with its parallel array structure is ideally suited for such computations. These preliminary results indicate that it is possible to use the MEM method in future coded-aperture experiments with the help of the MPP.

Bielefeld, Michael J.

Coded aperture imaging - Predicted performance of uniformly redundant arrays

It is noted that uniformly redundant arrays (URAs) have autocorrelation functions with perfectly flat sidelobes. A generalized signal-to-noise equation has been developed to predict URA performance. The signal-to-noise value is formulated as a function of aperture transmission or density, the ratio of the intensity of a resolution element to the integrated source intensity, and the ratio of detector background noise to the integrated intensity. It is shown that the only two-dimensional URAs known have a transmission of one half. This is not a great limitation because a nonoptimum transmission of one half never reduces the signal-to-noise ratio more than 30%. The reconstructed URA image contains practically uniform noise, regardless of the object structure. URA's improvement over the single-pinhole camera is much larger for high-intensity points than for low-intensity points.

Fenimore, E. E.

Recent developments at JPL in the application of image processing to astronomy

Four applications of image processing to astronomy, automated location and analysis of star and galaxy images, geometric and radiometric decalibration of vidicon spectra, display of multiband radio images, and generation of high resolution polarization direction and magnitude maps from images are presented with illustrative examples. The technique by which a digital image can be analyzed automatically to locate and segregate between stars and galaxies and the steps performed by the classifier to determine the nature of each object are outlined. The classification program executed on a 48 inch Schmidt plate of the cluster of galaxies 655 is described. The calibration and decalibration steps to remove geometric and radiometric distortions from a silicon vidicon camera digital spectra are discussed. Three methods of displaying multispectral radio data, generating a mosaic of each image, producing a color coded image to depict radio velocity, and producing a stereo pair with radial velocity as depth are described. The generation of polarization information from images obtained through linear polarizing filters is illustrated, and it is concluded that in each case information was displayed using digital techniques which could not readily have been provided visually.

Lorre, J. J.

Emerging standards for still image compression: A software implementation and simulation study

The software implementation is described of an emerging standard for the lossy compression of continuous tone still images. This software program can be used to compress planetary images and other 2-D instrument data. It provides a high compression image coding capability that preserves image fidelity at compression rates competitive or superior to most known techniques. This software implementation confirms the usefulness of such data compression and allows its performance to be compared with other schemes used in deep space missions and for data based storage.

Pollara, F.

Techniques for removing non-uniform background in coded-aperture imaging on the energetic X-ray imaging telescope experiment

It is found that the subtractive flat field technique for nonuniform background illumination is generally effective at removing background systematics for stationary mask experiments such as the Energetic X-ray Imaging Experiment. The time dependence of intensity and the two-dimensional shape of the background detector image during the flight are explored. A flat field image is constructed from observations where X-ray sources were absent from the field of view. It is shown that this technique can successfully reduce rms fluctuations to within a few percent of ideal Poisson statistics. The quality of the flat field does not appear to be a strong function of radius and can be used effectively out to the edge of the detector to remove the strong background ring.

Covault, C. E.

Coded Aperture Imaging

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Alvar Saenz-otero

Spatial transform coding of color images.

The application of the transform-coding concept to the coding of color images represented by three primary color planes of data is discussed. The principles of spatial transform coding are reviewed and the merits of various methods of color-image representation are examined. A performance analysis is presented for the color-image transform-coding system. Results of a computer simulation of the coding system are also given. It is shown that, by transform coding, the chrominance content of a color image can be coded with an average of 1.0 bits per element or less without serious degradation. If luminance coding is also employed, the average rate reduces to about 2.0 bits per element or less.

Pratt, W. K.

Information theoretical assessment of image gathering and coding for digital restoration

The process of image-gathering, coding, and restoration is presently treated in its entirety rather than as a catenation of isolated tasks, on the basis of the relationship between the spectral information density of a transmitted signal and the restorability of images from the signal. This 'information-theoretic' assessment accounts for the information density and efficiency of the acquired signal as a function of the image-gathering system's design and radiance-field statistics, as well as for the information efficiency and data compression that are obtainable through the combination of image gathering with coding to reduce signal redundancy. It is found that high information efficiency is achievable only through minimization of image-gathering degradation as well as signal redundancy.

Huck, Friedrich O.

Image gathering and coding for digital restoration: Information efficiency and visual quality

Image gathering and coding are commonly treated as tasks separate from each other and from the digital processing used to restore and enhance the images. The goal is to develop a method that allows us to assess quantitatively the combined performance of image gathering and coding for the digital restoration of images with high visual quality. Digital restoration is often interactive because visual quality depends on perceptual rather than mathematical considerations, and these considerations vary with the target, the application, and the observer. The approach is based on the theoretical treatment of image gathering as a communication channel (J. Opt. Soc. Am. A2, 1644(1985);5,285(1988). Initial results suggest that the practical upper limit of the information contained in the acquired image data range typically from approximately 2 to 4 binary information units (bifs) per sample, depending on the design of the image-gathering system. The associated information efficiency of the transmitted data (i.e., the ratio of information over data) ranges typically from approximately 0.3 to 0.5 bif per bit without coding to approximately 0.5 to 0.9 bif per bit with lossless predictive compression and Huffman coding. The visual quality that can be attained with interactive image restoration improves perceptibly as the available information increases to approximately 3 bifs per sample. However, the perceptual improvements that can be attained with further increases in information are very subtle and depend on the target and the desired enhancement.

Huck, Friedrich O.

Neural networks for data compression and invariant image recognition

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

Gardner, Sheldon