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NASA NTRS1993

High-performance compression of astronomical images

Astronomical images have some rather unusual characteristics that make many existing image compression techniques either ineffective or inapplicable. A typical image consists of a nearly flat background sprinkled with point sources and occasional extended sources. The images are often noisy, so that lossless compression does not work very well; furthermore, the images are usually subjected to stringent quantitative analysis, so any lossy compression method must be proven not to discard useful information, but must instead discard only the noise. Finally, the images can be extremely large. For example, the Space Telescope Science Institute has digitized photographic plates covering the entire sky, generating 1500 images each having 14000 x 14000 16-bit pixels. Several astronomical groups are now constructing cameras with mosaics of large CCD's (each 2048 x 2048 or larger); these instruments will be used in projects that generate data at a rate exceeding 100 MBytes every 5 minutes for many years. An effective technique for image compression may be based on the H-transform (Fritze et al. 1977). The method that we have developed can be used for either lossless or lossy compression. The digitized sky survey images can be compressed by at least a factor of 10 with no noticeable losses in the astrometric and photometric properties of the compressed images. The method has been designed to be computationally efficient: compression or decompression of a 512 x 512 image requires only 4 seconds on a Sun SPARCstation 1. The algorithm uses only integer arithmetic, so it is completely reversible in its lossless mode, and it could easily be implemented in hardware for space applications.

White, Richard L.↗

NASA NTRS1994

Improved image decompression for reduced transform coding artifacts

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Orourke, Thomas P.↗

NASA NTRS1998

Magnetospheric Image Unfolding

The Grant was a three year grant funded under the Space Physics Supporting Research and Technology and Suborbital Program. Our objective was to develop automated techniques needed to unfold or "invert" global images of the magnetospheric ion populations obtained by the new magnetospheric imaging techniques (ENA, EUV) in anticipation of future missions such as the Magnetospheric Imager and, now, IMAGE. Our focus on the present three year grant is to determine the degree to which such images can quantitatively constrain the global electromagnetic properties of the magnetosphere. In a previous three year grant period we successfully automated a forward modeling inversion algorithm, demonstrated that these inversions are robust in the face of realistic instrumental considerations such as counting statistics and backgrounds, applied error analysis techniques to the extracted parameters using variational procedures, implemented very realistic magnetospheric test images to test the inversion algorithms using the Rice University Magnetospheric Specification Model, and began the process of generating parametric models with the flexibility to handle the realistic magnetospheric images (e.g. Roelof et al, 1992; 1993). Our plan for the present 3 year grant period was to complete the development of the inversion tools needed to handle realistic magnetospheric images, assess the degree to which global electrodynamics is quantitatively constrained by ENA images of the magnetosphere, and bring the inversion of EUV images up to the maturity that we will have achieved for the ENA imaging. Below the accomplishments of our three year effort are present followed by a list of our presentations and publications. The accomplishments of all three years are presented here, and thus some of these items appeared on interim progress reports.

Source record↗

NASA NTRS1998

Neutral Networks for Subpixel Classification of Multispectral Images

In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.

Figueroa, Ricardo R.↗

NASA NTRS1999

Autonomous Image Analysis for Future Mars Missions

To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to preferentially transmit "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high-resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. We are currently investigating the possibility of reconstructing a 3D surface from a sequence of images acquired by a robotic arm camera. This would then allow the return of a single completely in focus image constructed only from those portions of individual images that lie within the camera's depth of field. Output from these algorithms could be used to autonomously obtain rock spectra, determine which images should be transmitted to the ground, or to aid in image compression. We will discuss these algorithms and their performance during a recent rover field test.

Gulick, V. C.↗

NASA NTRS1996

Perceptual Image Compression in Telemedicine

The next era of space exploration, especially the "Mission to Planet Earth" will generate immense quantities of image data. For example, the Earth Observing System (EOS) is expected to generate in excess of one terabyte/day. NASA confronts a major technical challenge in managing this great flow of imagery: in collection, pre-processing, transmission to earth, archiving, and distribution to scientists at remote locations. Expected requirements in most of these areas clearly exceed current technology. Part of the solution to this problem lies in efficient image compression techniques. For much of this imagery, the ultimate consumer is the human eye. In this case image compression should be designed to match the visual capacities of the human observer. We have developed three techniques for optimizing image compression for the human viewer. The first consists of a formula, developed jointly with IBM and based on psychophysical measurements, that computes a DCT quantization matrix for any specified combination of viewing distance, display resolution, and display brightness. This DCT quantization matrix is used in most recent standards for digital image compression (JPEG, MPEG, CCITT H.261). The second technique optimizes the DCT quantization matrix for each individual image, based on the contents of the image. This is accomplished by means of a model of visual sensitivity to compression artifacts. The third technique extends the first two techniques to the realm of wavelet compression. Together these two techniques will allow systematic perceptual optimization of image compression in NASA imaging systems. Many of the image management challenges faced by NASA are mirrored in the field of telemedicine. Here too there are severe demands for transmission and archiving of large image databases, and the imagery is ultimately used primarily by human observers, such as radiologists. In this presentation I will describe some of our preliminary explorations of the applications of our technology to the special problems of telemedicine.

Watson, Andrew B.↗

NASA NTRS2002

Image Dis-Integration for Improved Plasmasphere Visualization

Traditionally, study of the plasmasphere has involved terrestrial observation of local characteristics. Global modeling of the plasmasphere in such an observation regime made use of an ensemble of (sparse) local measurements. Recently, sensors aboard the IMAGE (Imager for Magnetopause-to-Aurora Global Exploration) satellite (in particular, the EUV (Extreme Ultra Violet) Imager) have created the potential for truly global study of the plasmasphere. IMAGE was launched in spring of 2000 in an orbit with apogee altitude 7.2 R E (Earth radii) and perigee altitude 1000 km. IMAGE's EUV sensor allows an external view of the distribution of cold plasma in the plasmasphere to be acquired. EUV is designed to image light emission at 30.4 nanometers, which is the emission wavelength of the He + ion in the presence of solar radiation. He + makes up approximately 15-20% of the plasma in the plasmasphere, thus imaging of He + enables determination of plasma distribution. The EUV instrument provides a 90° by 84° field of view which is imaged as an equally spaced 150x140 pixel array on a spherical imaging surface. The EUV produces an image approximately every 10 minutes when the sensor is operating. Since EUV images contain line-of-sight integrations of plasma distributions, they do not directly express equatorial plane density (which would enable comparison of observed plasma distributions with predictions from models). Furthermore, the plasma density at any point in three-space is not known. The goal of our work was development of a technique that can enable plasma density to be determined throughout three-space. Our approach to creation of a three-space representation of the plasma distribution involves disintegrating the EUV lines of sight to form a volumetric map of plasma densities.

Timothy S. Newman↗

NASA NTRS2003

Parallel Information Processing (Image Transmission Via Fiber Bundle and Multimode Fiber

Growing demand for visual, user-friendly representation of information inspires search for the new methods of image transmission. Currently used in-series (sequential) methods of information processing are inherently slow and are designed mainly for transmission of one or two dimensional arrays of data. Conventional transmission of data by fibers requires many fibers with array of laser diodes and photodetectors. In practice, fiber bundles are also used for transmission of images. Image is formed on the fiber-optic bundle entrance surface and each fiber transmits the incident image to the exit surface. Since the fibers do not preserve phase, only 2D intensity distribution can be transmitted in this way. Each single mode fiber transmit only one pixel of an image. Multimode fibers may be also used, so that each mode represent different pixel element. Direct transmission of image through multimode fiber is hindered by the mode scrambling and phase randomization. To overcome these obstacles wavelength and time-division multiplexing have been used, with each pixel transmitted on a separate wavelength or time interval. Phase-conjugate techniques also was tested in, but only in the unpractical scheme when reconstructed image return back to the fiber input end. Another method of three-dimensional imaging over single mode fibers was demonstrated in, using laser light of reduced spatial coherence. Coherence encoding, needed for a transmission of images by this methods, was realized with grating interferometer or with the help of an acousto-optic deflector. We suggest simple practical holographic method of image transmission over single multimode fiber or over fiber bundle with coherent light using filtering by holographic optical elements. Originally this method was successfully tested for the single multimode fiber. In this research we have modified holographic method for transmission of laser illuminated images over commercially available fiber bundle (fiber endoscope, or fiberscope).

Kukhtarev, Nicholai↗

NASA NTRS2002

Multi-Image Registration for an Enhanced Vision System

An Enhanced Vision System (EVS) utilizing multi-sensor image fusion is currently under development at the NASA Langley Research Center. The EVS will provide enhanced images of the flight environment to assist pilots in poor visibility conditions. Multi-spectral images obtained from a short wave infrared (SWIR), a long wave infrared (LWIR), and a color visible band CCD camera, are enhanced and fused using the Retinex algorithm. The images from the different sensors do not have a uniform data structure: the three sensors not only operate at different wavelengths, but they also have different spatial resolutions, optical fields of view (FOV), and bore-sighting inaccuracies. Thus, in order to perform image fusion, the images must first be co-registered. Image registration is the task of aligning images taken at different times, from different sensors, or from different viewpoints, so that all corresponding points in the images match. In this paper, we present two methods for registering multiple multi-spectral images. The first method performs registration using sensor specifications to match the FOVs and resolutions directly through image resampling. In the second method, registration is obtained through geometric correction based on a spatial transformation defined by user selected control points and regression analysis.

Hines, Glenn↗

NASA NTRS2004

SILVER: Surface Imaging for Lunar Volatiles, Resources, and Exploration

The Surface Imaging for Lunar Volatiles, Exploration, and Resources (SILVER) instrument is a proposed imaging investigation for the 2008 Lunar Reconnaissance Orbiter (LRO) mission. SILVER and its experienced Measurement Team will prepare for and support future lunar human exploration activities, especially landing site identification and certification on the basis of potential resources. SILVER combines a high-resolution pushbroom visible imaging channel (SILVER-HR) and a wide-field-of-view (45 deg) framing imaging channel (SILVER-WF). SILVER-HR will obtain a single-detector 6 km imaging swath of 12,228 pixels at 0.5 m/pixel to image greater than 100 sq km target areas from 50 km altitude, imaging greater than 15% the lunar surface during a 1 year nominal mission. SILVER-HR has excellent stray-light rejection and its imaging detector has selectable time delay integration (TDI) with up to 128 stages for extreme low-light sensitivity, permitting direct imaging of permanently shadowed polar regions in scattered sunlight or earthshine. SILVER-WF will obtain geodetic framing images in a 2048 x 2048 format at 20m/pixel, with 60% along-track overlap stereo for imaging context and for derivation of a global digital elevation model of meter-scale lunar topography.

Pappalardo, R. T.↗

NASA NTRS1999

Tracker: Image-Processing and Object-Tracking System Developed

Tracker is an object-tracking and image-processing program designed and developed at the NASA Lewis Research Center to help with the analysis of images generated by microgravity combustion and fluid physics experiments. Experiments are often recorded on film or videotape for analysis later. Tracker automates the process of examining each frame of the recorded experiment, performing image-processing operations to bring out the desired detail, and recording the positions of the objects of interest. It can load sequences of images from disk files or acquire images (via a frame grabber) from film transports, videotape, laser disks, or a live camera. Tracker controls the image source to automatically advance to the next frame. It can employ a large array of image-processing operations to enhance the detail of the acquired images and can analyze an arbitrarily large number of objects simultaneously. Several different tracking algorithms are available, including conventional threshold and correlation-based techniques, and more esoteric procedures such as "snake" tracking and automated recognition of character data in the image. The Tracker software was written to be operated by researchers, thus every attempt was made to make the software as user friendly and self-explanatory as possible. Tracker is used by most of the microgravity combustion and fluid physics experiments performed by Lewis, and by visiting researchers. This includes experiments performed on the space shuttles, Mir, sounding rockets, zero-g research airplanes, drop towers, and ground-based laboratories. This software automates the analysis of the flame or liquid s physical parameters such as position, velocity, acceleration, size, shape, intensity characteristics, color, and centroid, as well as a number of other measurements. It can perform these operations on multiple objects simultaneously. Another key feature of Tracker is that it performs optical character recognition (OCR). This feature is useful in extracting numerical instrumentation data that are embedded in images. All the results are saved in files for further data reduction and graphing. There are currently three Tracking Systems (workstations) operating near the laboratories and offices of Lewis Microgravity Science Division researchers. These systems are used independently by students, scientists, and university-based principal investigators. The researchers bring their tapes or films to the workstation and perform the tracking analysis. The resultant data files generated by the tracking process can then be analyzed on the spot, although most of the time researchers prefer to transfer them via the network to their offices for further analysis or plotting. In addition, many researchers have installed Tracker on computers in their office for desktop analysis of digital image sequences, which can be digitized by the Tracking System or some other means. Tracker has not only provided a capability to efficiently and automatically analyze large volumes of data, saving many hours of tedious work, but has also provided new capabilities to extract valuable information and phenomena that was heretofore undetected and unexploited.

Klimek, Robert B.↗

NASA NTRS1999

Image transfer protocol in progressively increasing resolution

A method of transferring digital image data over a communication link transforms and orders the data so that, as data is received by a receiving station, a low detail version of the image is immediately generated with later transmissions of data providing progressively greater detail in this image. User instructions are accepted, limiting the ultimate resolution of the image or suspending enhancement of the image except in certain user defined regions. When a low detail image is requested followed by a request for a high detailed version of the same image, the originally transmitted data of the low resolution image is not discarded or retransmitted but used with later data to improve the originally transmitted image. Only a single copy of the transformed image need be retained by the transmitting device in order to satisfy requests for different amounts of image detail.

Percival, Jeffrey W.↗

NASA NTRS1998

Image compression system and method having optimized quantization tables

A digital image compression preprocessor for use in a discrete cosine transform-based digital image compression device is provided. The preprocessor includes a gathering mechanism for determining discrete cosine transform statistics from input digital image data. A computing mechanism is operatively coupled to the gathering mechanism to calculate a image distortion array and a rate of image compression array based upon the discrete cosine transform statistics for each possible quantization value. A dynamic programming mechanism is operatively coupled to the computing mechanism to optimize the rate of image compression array against the image distortion array such that a rate-distortion-optimal quantization table is derived. In addition, a discrete cosine transform-based digital image compression device and a discrete cosine transform-based digital image compression and decompression system are provided. Also, a method for generating a rate-distortion-optimal quantization table, using discrete cosine transform-based digital image compression, and operating a discrete cosine transform-based digital image compression and decompression system are provided.

Ratnakar, Viresh↗

NASA NTRS2006

System and method for improving ultrasound image acquisition and replication for repeatable measurements of vascular structures

High resolution B-mode ultrasound images of the common carotid artery are obtained with an ultrasound transducer using a standardized methodology. Subjects are supine with the head counter-rotated 45 degrees using a head pillow. The jugular vein and carotid artery are located and positioned in a vertical stacked orientation. The transducer is rotated 90 degrees around the centerline of the transverse image of the stacked structure to obtain a longitudinal image while maintaining the vessels in a stacked position. A computerized methodology assists operators to accurately replicate images obtained over several spaced-apart examinations. The methodology utilizes a split-screen display in which the arterial ultrasound image from an earlier examination is displayed on one side of the screen while a real-time live ultrasound image from a current examination is displayed next to the earlier image on the opposite side of the screen. By viewing both images, whether simultaneously or alternately, while manually adjusting the ultrasound transducer, an operator is able to bring into view the real-time image that best matches a selected image from the earlier ultrasound examination. Utilizing this methodology, measurement of vascular dimensions such as carotid arterial IMT and diameter, the coefficient of variation is substantially reduced to values approximating from about 1.0% to about 1.25%. All images contain anatomical landmarks for reproducing probe angulation, including visualization of the carotid bulb, stacking of the jugular vein above the carotid artery, and initial instrumentation settings, used at a baseline measurement are maintained during all follow-up examinations.

Selzer, Robert H.↗

NASA NTRS2010

Interference-free ultrasound imaging during HIFU therapy, using software tools

Disclosed herein is a method for obtaining a composite interference-free ultrasound image when non-imaging ultrasound waves would otherwise interfere with ultrasound imaging. A conventional ultrasound imaging system is used to collect frames of ultrasound image data in the presence of non-imaging ultrasound waves, such as high-intensity focused ultrasound (HIFU). The frames are directed to a processor that analyzes the frames to identify portions of the frame that are interference-free. Interference-free portions of a plurality of different ultrasound image frames are combined to generate a single composite interference-free ultrasound image that is displayed to a user. In this approach, a frequency of the non-imaging ultrasound waves is offset relative to a frequency of the ultrasound imaging waves, such that the interference introduced by the non-imaging ultrasound waves appears in a different portion of the frames.

Vaezy, Shahram↗

NASA NTRS2011

CMOS Imager Has Better Cross-Talk and Full-Well Performance

A complementary metal oxide/semiconductor (CMOS) image detector now undergoing development is designed to exhibit less cross-talk and greater full-well capacity than do prior CMOS image detectors of the same type. Imagers of the type in question are designed to operate from low-voltage power supplies and are fabricated by processes that yield device features having dimensions in the deep submicron range. Because of the use of low supply potentials, maximum internal electric fields and depletion widths are correspondingly limited. In turn, these limitations are responsible for increases in cross-talk and decreases in charge-handling capacities. Moreover, for small pixels, lateral depletion cannot be extended. These adverse effects are even more accentuated in a back-illuminated CMOS imager, in which photogenerated charge carriers must travel across the entire thickness of the device. The figure shows a partial cross section of the structure in the device layer of the present developmental CMOS imager. (In a practical imager, the device layer would sit atop either a heavily doped silicon substrate or a thin silicon oxide layer on a silicon substrate, not shown here.) The imager chip is divided into two areas: area C, which contains readout circuits and other electronic circuits; and area I, which contains the imaging (photodetector and photogenerated-charge-collecting) pixel structures. Areas C and I are electrically isolated from each other by means of a trench filled with silicon oxide. The electrical isolation between areas C and I makes it possible to apply different supply potentials to these areas, thereby enabling optimization of the supply potential and associated design features for each area. More specifically, metal oxide semiconductor field-effect transistors (MOSFETs) that are typically included in CMOS imagers now reside in area C and can remain unchanged from established designs and operated at supply potentials prescribed for those designs, while the dopings and the lower supply potentials in area I can be tailored to optimize imager performance. In area I, the device layer includes an n+ -doped silicon layer on which is grown an n-doped silicon layer. A p-doped silicon layer is grown on top of the n -doped layer. The total imaging device thickness is the sum of the thickness of the n+, n, and p layers. A pixel photodiode is formed between a surface n+ implant, a p implant underneath it, the aforementioned p layer, and the n and n+ layers. Adjacent to the diode is a gate for transferring photogenerated charges out of the photodiode and into a floating diffusion formed by an implanted p+ layer on an implanted n-doped region. Metal contact pads are added to the back-side for providing back-side bias.

Pain, Bedabrata↗

NASA NTRS2005

Multipurpose Hyperspectral Imaging System

A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral imaging with or without relative movement of the imaging system, and it can be used to scan a target of any size as long as the target can be imaged at the focal plane; for example, automated inspection of food items and identification of single-celled organisms. The spectral resolution of this system is greater than that of prior terrestrial multispectral imaging systems. Moreover, unlike prior high-spectral resolution airborne and spaceborne hyperspectral imaging systems, this system does not rely on relative movement of the target and the imaging system to sweep an imaging line across a scene. This compact system (see figure) consists of a front objective mounted at a translation stage with a motorized actuator, and a line-slit imaging spectrograph mounted within a rotary assembly with a rear adaptor to a charged-coupled-device (CCD) camera. Push-broom scanning is carried out by the motorized actuator which can be controlled either manually by an operator or automatically by a computer to drive the line-slit across an image at a focal plane of the front objective. To reduce the cost, the system has been designed to integrate as many as possible off-the-shelf components including the CCD camera and spectrograph. The system has achieved high spectral and spatial resolutions by using a high-quality CCD camera, spectrograph, and front objective lens. Fixtures for attachment of the system to a microscope (U.S. Patent 6,495,818 B1) make it possible to acquire multispectral images of single cells and other microscopic objects.

Mao, Chengye↗

NASA NTRS2011

Extended depth of field imaging for high speed object analysis

A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.

Ortyn, William↗