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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Voyager Cartography

The Jovian and Saturnian satellites are being mapped at several scales from Voyager 1 and 2 data. The maps include specially formatted color mosaics, controlled photomosaics, and airbrush maps. More than 500 Voyager images of the Jovian and Saturnian satellites were radiometrically processed in preparation for cartographic processing. Of these images, 235 were geometrically transformed to map projections for base mosaic compilations. Special techniques for producing hybrid photomosaic/airbrush maps of Callisto are under investigation. The techniques involve making controlled computer mosaics of all available images with highest resolution images superimposed on lowest resolution images. The mosaics are then improved by airbrushing: seams and artifacts are removed, and image details enhanced that had been lost by saturation in some images. A controlled mosaic of the northern hemisphere of Rhea is complete, as is all processing for a similar mosaic of the equatorial region. Current plans and status of the various series are shown in a table.

Batson, R. M.↗
NASA NTRS1985

Graphic displays of vector magnetograph data

Graphic displays that have proved useful in dealing with vector magnetograph data are summarized in three settings: real-time control, analysis, and final presentation. Among the topics discussed are: flexible, implicit data-scaling; geometrical transformations; methods of comparing fields (e.g., transverse vs. longitudinal; observed vs. computed; one time vs. another); displaying the magnitude and direction of the transverse field; minimizing the display time of serial graphics devices; graphic file structure; and graphic interaction with operators and observers.

Rabin, D. M.↗
NASA NTRS1984

Registering Thematic Mapper imagery to digital elevation models

The problems encountered when attempting to register Landsat Thematic Mapper (TM) data to U.S. geological survey digital elevation models (DEMs) are examined. It is shown that TM and DEM data are not available in the same map projection, necessitating geometric transformation of one of the data type, that the TM data are not accurately located in their nominal projection, and that TM data have higher resolution than most DEM data, but oversampling the DEM data to TM resolution introduces systematic noise. Further work needed in this area is discussed.

Frew, J.↗
NASA NTRS1987

Cartography of irregularly shaped satellites

Irregularly shaped satellites, such as Phobos and Amalthea, do not lend themselves to mapping by conventional methods because mathematical projections of their surfaces fail to convey an accurate visual impression of the landforms, and because large and irregular scale changes make their features difficult to measure on maps. A digital mapping technique has therefore been developed by which maps are compiled from digital topographic and spacecraft image files. The digital file is geometrically transformed as desired for human viewing, either on video screens or on hard copy. Digital files of this kind consist of digital images superimposed on another digital file representing the three-dimensional form of a body.

Batson, R. M.↗
NASA NTRS1987

Geometric processing of digital images of the planets

New procedures and software have been developed for geometric transformation of images to support digital cartography of the planets. The procedures involve the correction of spacecraft camera orientation of each image with the use of ground control and the transformation of each image to a Sinusoidal Equal-Area map projection with an algorithm which allows the number of transformation calculations to vary as the distortion varies within the image. When the distortion is low in an area of an image, few transformation computations are required, and most pixels can be interpolated. When distortion is extreme, the location of each pixel is computed. Mosaics are made of these images and stored as digital databases. Completed Sinusoidal databases may be used for digital analysis and registration with other spatial data. They may also be reproduced as published image maps by digitally transforming them to appropriate map projections.

Edwards, Kathleen↗
NASA NTRS1988

Image processing in optical astronomy

Successful efforts to enhance optical-astronomy images through digital processing often exploit such 'weaknesses' of the image as the objects' near-symmetry, their preferred directionality, or a differentiation in spatial frequency between the object or objects and superimposed clutter. Attention is presently given to the calibration of a camera prior to astronomical data-acquisition, methods for the enhancement of faint surface brightness features, automated target detection and extraction techniques, the importance of the geometric transformations of digital imagery, the preparation of two-dimensional histograms, and the application of polarization.

Lorre, Jean J.↗
NASA NTRS1989

Optical pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

Papers on optical pattern recognition are presented, covering topics such as the estimation of satellite pose and motion parameters using a neural net tracker, associative memory, optical implmentation of programmable neural networks, optoelectronic neural networks, dynamic autoassociative neural memory, heteroassociative memory, bilinear pattern recognition processors, optical processing of optical correlation plane data, and a synthetic discriminant function-based nonlinear optical correlator. Other topics include an interactive optical-digital image processor, geometric transformations for video compression and human teleoperator display, quasiconformal remapping for compensation of human visual field defects, hybrid vision for automated spacecraft landing, advanced symbolic and inference optical correlation filters, and a rotationally invariant holographic tracking system. Additional topics include the detection of rotational and scale-varying objects with a programmable joint transform correlator, a single spatial light modulator binary nonlinear optical correlator, optical joint transform correlation, linear phase coefficient composite filters, and binary phase-only filters.

Liu, Hua-Kuang↗
NASA NTRS1990

Connectivity strategies for higher-order neural networks applied to pattern recognition

Different strategies for non-fully connected HONNs (higher-order neural networks) are discussed, showing that by using such strategies an input field of 128 x 128 pixels can be attained while still achieving in-plane rotation and translation-invariant recognition. These techniques allow HONNs to be used with the larger input scenes required for practical pattern-recognition applications. The number of interconnections that must be stored has been reduced by a factor of approximately 200,000 in a T/C case and about 2000 in a Space Shuttle/F-18 case by using regional connectivity. Third-order networks have been simulated using several connection strategies. The method found to work best is regional connectivity. The main advantages of this strategy are the following: (1) it considers features of various scales within the image and thus gets a better sample of what the image looks like; (2) it is invariant to shape-preserving geometric transformations, such as translation and rotation; (3) the connections are predetermined so that no extra computations are necessary during run time; and (4) it does not require any extra storage for recording which connections were formed.

Spirkovska, Lilly↗
NASA NTRS1991

On an adaptive truss manipulator space crane concept

The paper describes an adaptive truss manipulator (ATM) space crane concept for in-space assembly and construction. The underlying mechanism of an ATM is that the batten members of the constituent octahedral modules are controllable in length. Through geometric transformations of the constituent modules, the basic manipulator functions such as articulation can be performed by the ATM. The mechanism can also provide deployment/retraction, high dexterity motion, and bracing operation. The advantages of an ATM over the conventional multijoint-multilink anthropomorphic manipulator are its compact stowage volume for in-space storage and mobility, deployment as needed, high dexterity in complex workspace, and high redundancy of the actuator function. The kinematic description of an ATM is formulated in the global cartesian coordinate system.

Chen, Gun-Shing↗
NASA NTRS1993

Interim report on Landsat national archive activities

The Department of the Interior (DOI) has the responsibility to preserve and to distribute most Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) data that have been acquired by the five Landsat satellites operational since July 1972. Data that are still covered by exclusive marketing rights, which were granted by the U.S. Government to the commercial Landsat operator, cannot be distributed by the DOI. As the designated national archive for Landsat data, the U.S. Geological Survey's EROS Data Center (EDC) has initiated two new programs to protect and make available any of the 625,000 MSS scenes currently archived and the 200,000 TM scenes to be archived at EDC by 1995. A specially configured system has begun converting Landsat MSS data from obsolete high density tapes (HDT's) to more dense digital cassette tapes. After transcription, continuous satellite swaths are (1) divided into standard scenes defined by a world reference system, (2) geographically located by latitude and longitude, and (3) assessed for overall quality. Digital browse images are created by subsampling the full-resolution swaths. Conversion of the TM HDT's will begin in the fourth quarter of 1992 and will be conducted concurrently with MSS conversion. Although the TM archive is three times larger than the entire MSS archive, conversion of data from both sensor systems and consolidation of the entire Landsat archive at EDC will be completed by the end of 1994. Some MSS HDT's have deteriorated, primarily as a result of hydrolysis of the pigment binder. Based on a small sample of the 11 terabytes of post-1978 MSS data and the 41 terabytes of TM data to be converted, it appears that to date, less than 2 percent of the data have been lost. The data loss occurs within small portions of some scenes; few scenes are lost entirely. Approximately 10,000 pre-1979 MSS HDT's have deteriorated to such an extent, as a result of hydrolysis, that the data cannot be recovered without special treatment of the tapes. An independent consulting division of a major tape manufacturer has analyzed affected tapes and is confident that restorative procedures can be applied to the HDT's to permit one pass to reproduce the data on another recording media. A system to distribute minimally processed Landsat data will be procured in 1992 and will be operational by mid-1994. Any TM or MSS data in the national archive that are not restricted by exclusive marketing rights will be reproduced directly from the archive media onto user specified computer-compatible media. TM data will be produced either at a raw level (radiometrically and geometrically uncorrected) or at an intermediate level (radiometrically corrected and geometrically indexed). MSS data will be produced to an intermediate level or to a fully corrected level (radiometrically corrected and geometrically transformed to an Oblique Mercator projection). The system will be capable of providing ordered scenes within 48 hours of receipt of order.

Boyd, John E.↗
NASA NTRS1991

VLSI architectures for geometrical mapping problems in high-definition image processing

This paper explores a VLSI architecture for geometrical mapping address computation. The geometric transformation is discussed in the context of plane projective geometry, which invokes a set of basic transformations to be implemented for the general image processing. The homogeneous and 2-dimensional cartesian coordinates are employed to represent the transformations, each of which is implemented via an augmented CORDIC as a processing element. A specific scheme for a processor, which utilizes full-pipelining at the macro-level and parallel constant-factor-redundant arithmetic and full-pipelining at the micro-level, is assessed to produce a single VLSI chip for HDTV applications using state-of-art MOS technology.

Kim, K.↗
NASA NTRS1992

PCIPS 2.0: Powerful multiprofile image processing implemented on PCs

Over the years, the processing power of personal computers has steadily increased. Now, 386- and 486-based PC's are fast enough for many image processing applications, and inexpensive enough even for amateur astronomers. PCIPS is an image processing system based on these platforms that was designed to satisfy a broad range of data analysis needs, while requiring minimum hardware and providing maximum expandability. It will run (albeit at a slow pace) even on a 80286 with 640K memory, but will take full advantage of bigger memory and faster CPU's. Because the actual image processing is performed by external modules, the system can be easily upgraded by the user for all sorts of scientific data analysis. PCIPS supports large format lD and 2D images in any numeric type from 8-bit integer to 64-bit floating point. The images can be displayed, overlaid, printed and any part of the data examined via an intuitive graphical user interface that employs buttons, pop-up menus, and a mouse. PCIPS automatically converts images between different types and sizes to satisfy the requirements of various applications. PCIPS features an API that lets users develop custom applications in C or FORTRAN. While doing so, a programmer can concentrate on the actual data processing, because PCIPS assumes responsibility for accessing images and interacting with the user. This also ensures that all applications, even custom ones, have a consistent and user-friendly interface. The API is compatible with factory programming, a metaphor for constructing image processing procedures that will be implemented in future versions of the system. Several application packages were created under PCIPS. The basic package includes elementary arithmetics and statistics, geometric transformations and import/export in various formats (FITS, binary, ASCII, and GIF). The CCD processing package and the spectral analysis package were successfully used to reduce spectra from the Nordic Telescope at La Palma. A photometry package is also available, and other packages are being developed. A multitasking version of PCIPS that utilizes the factory programming concept is currently under development. This version will remain compatible (on the source code level) with existing application packages and custom applications.

Smirnov, O. M.↗
NASA NTRS1994

Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

Spirkovska, Lilly↗
NASA NTRS2003

Use of Multi-Resolution Wavelet Feature Pyramids for Automatic Registration of Multi-Sensor Imagery

The problem of image registration, or alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times, and that would provide sub-pixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the band-pass wavelets obtained from the Steerable Pyramid due to Simoncelli perform better than two types of low-pass pyramids when the images being registered have relatively small amount of nonlinear radiometric variations between them. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Zavorin, Ilya↗
NASA NTRS2005

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies↗
NASA NTRS2007

Research Issues in Image Registration for Remote Sensing

Image registration is an important element in data processing for remote sensing with many applications and a wide range of solutions. Despite considerable investigation the field has not settled on a definitive solution for most applications and a number of questions remain open. This article looks at selected research issues by surveying the experience of operational satellite teams, application-specific requirements for Earth science, and our experiments in the evaluation of image registration algorithms with emphasis on the comparison of algorithms for subpixel accuracy. We conclude that remote sensing applications put particular demands on image registration algorithms to take into account domain-specific knowledge of geometric transformations and image content.

Eastman, Roger D.↗
NASA NTRS2013

Building a 2.5D Digital Elevation Model from 2D Imagery

When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in a standard DEM format and used for projection.

Padgett, Curtis W.↗
NASA NTRS2017

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (Invited)

Many land applications require more frequent observations than can be obtained from a single 'Landsat class' sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a '30-meter MODIS' global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for approximately 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018. This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Reflectance↗