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At least 55 records · Page 3

Image Station Matching, Preprocessing, Spatial Registration and Change Detection with Multi-Temporal Remotely-Sensed Imagery

A method for collecting and processing remotely sensed imagery in order to achieve precise spatial co-registration (e.g., matched alignment) between multi-temporal image sets is presented. Such precise alignment or spatial co-registration of imagery can be used for change detection, image fusion, and temporal analysis/modeling. Further, images collected in this manner may be further processed in such a way that image frames or line arrays from corresponding photo stations are matched, co-aligned and if desired merged into a single image and/or subjected to the same processing sequence. A second methodology for automated detection of moving objects within a scene using a time series of remotely sensed imagery is also presented. Specialized image collection and preprocessing procedures are utilized to obtain precise spatial co-registration (image registration) between multitemporal image frame sets. In addition, specialized change detection techniques are employed in order to automate the detection of moving objects.

Coulter, Lloyd Lawrence Arthur↗

Planetary Crater Detection and Registration Using Marked Point Processes, Graph Cut Algorithms, and Wavelet Transforms

This paper addresses the problem of semi-automatic image registration on planetary images. A joint feature-based and area-based approach is proposed. Firstly, the most relevant craters are extracted from the two images to register, and then, registration is performed in two steps. The first step matches the craters extracted from the images based on a generalized Hausdorff distance. In the second step, the mutual information between the two images is maximized to achieve high registration accuracy. Craters are detected by a stochastic-geometry approach based on a marked point process model and of a multiple-birth-and-cut energy minimization algorithm. The experimental validation is carried out with 13 images for the crater extraction stage, and with 20 semi-synthetic pairs of images with ground truth and several images extracted from actual multi-temporal lunar scenes for the registration phase.

Image Processing; Pattern Recognition↗

Co-registration of Laser Altimeter Tracks with Digital Terrain Models and Applications in Planetary Science

We have derived algorithms and techniques to precisely co-register laser altimeter profiles with gridded Digital Terrain Models (DTMs), typically derived from stereo images. The algorithm consists of an initial grid search followed by a least-squares matching and yields the translation parameters at sub-pixel level needed to align the DTM and the laser profiles in 3D space. This software tool was primarily developed and tested for co-registration of laser profiles from the Lunar Orbiter Laser Altimeter (LOLA) with DTMs derived from the Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) stereo images. Data sets can be co-registered with positional accuracy between 0.13 m and several meters depending on the pixel resolution and amount of laser shots, where rough surfaces typically result in more accurate co-registrations. Residual heights of the data sets are as small as 0.18 m. The software can be used to identify instrument misalignment, orbit errors, pointing jitter, or problems associated with reference frames being used. Also, assessments of DTM effective resolutions can be obtained. From the correct position between the two data sets, comparisons of surface morphology and roughness can be made at laser footprint- or DTM pixel-level. The precise co-registration allows us to carry out joint analysis of the data sets and ultimately to derive merged high-quality data products. Examples of matching other planetary data sets, like LOLA with LRO Wide Angle Camera (WAC) DTMs or Mars Orbiter Laser Altimeter (MOLA) with stereo models from the High Resolution Stereo Camera (HRSC) as well as Mercury Laser Altimeter (MLA) with Mercury Dual Imaging System (MDIS) are shown to demonstrate the broad science applications of the software tool.

Laser↗

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

Fusion↗

Exploiting Measurement Uncertainty Estimation in Evaluation of GOES-R ABI Image Navigation Accuracy Using Image Registration Techniques

In evaluating GOES-R Advanced Baseline Imager (ABI) image navigation quality, upsampled sub-images of ABI images are translated against downsampled Landsat 8 images of localized, high contrast earth scenes to determine the translations in the East-West and North-South directions that provide maximum correlation. The native Landsat resolution is much finer than that of ABI, and Landsat navigation accuracy is much better than ABI required navigation accuracy and expected performance. Therefore, Landsat images are considered to provide ground truth for comparison with ABI images, and the translations of ABI sub-images that produce maximum correlation with Landsat localized images are interpreted as ABI navigation errors. The measured local navigation errors from registration of numerous sub-images with the Landsat images are averaged to provide a statistically reliable measurement of the overall navigation error of the ABI image. The dispersion of the local navigation errors is also of great interest, since ABI navigation requirements are specified as bounds on the 99.73rd percentile of the magnitudes of per pixel navigation errors. However, the measurement uncertainty inherent in the use of image registration techniques tends to broaden the dispersion in measured local navigation errors, masking the true navigation performance of the ABI system. We have devised a novel and simple method for estimating the magnitude of the measurement uncertainty in registration error for any pair of images of the same earth scene. We use these measurement uncertainty estimates to filter out the higher quality measurements of local navigation error for inclusion in statistics. In so doing, we substantially reduce the dispersion in measured local navigation errors, thereby better approximating the true navigation performance of the ABI system.

navigation performance↗

Correlation and registration of ERTS multispectral imagery

Examples of automatic digital processing demonstrate the feasibility of registering one ERTS multispectral scanner (MSS) image with another obtained on a subsequent orbit, and automatic matching, correlation, and registration of MSS imagery with aerial photography (multisensor correlation) is demonstrated. Excellent correlation was obtained with patch sizes exceeding 16 pixels square. Qualities which lead to effective control point selection are distinctive features, good contrast, and constant feature characteristics. Results of the study indicate that more than 300 degrees of freedom are required to register two standard ERTS-1 MSS frames covering 100 by 100 nautical miles to an accuracy of 0.6 pixel mean radial displacement error. An automatic strip processing technique demonstrates 600 to 1200 degrees of freedom over a quater frame of ERTS imagery. Registration accuracies in the range of 0.3 pixel to 0.5 pixel mean radial error were confirmed by independent error analysis. Accuracies in the range of 0.5 pixel to 1.4 pixel mean radial error were demonstrated by semi-automatic registration over small geographic areas.

Bonrud, L. O.↗

Image registration error variance as a measure of overlay quality

When one image (the signal) is to be registered with a second image (the signal plus noise) of the same scene, one would like to know the accuracy possible for this registration. This paper derives an estimate of the variance of the registration error that can be expected via two approaches. The solution in each instance is found to be a function of the effective bandwidth of the signal and the noise, and the signal-to-noise ratio. Application of these results to LANDSAT-1 data indicates that for most cases, registration variances will be significantly less than the diameter of one picture element.

Mcgillem, C. D.↗

Applications of digital image processing techniques to problems of data registration and correlation

An overview is presented of the evolution of the computer configuration at JPL's Image Processing Laboratory (IPL). The development of techniques for the geometric transformation of digital imagery is discussed and consideration is given to automated and semiautomated image registration, and the registration of imaging and nonimaging data. The increasing complexity of image processing tasks at IPL is illustrated with examples of various applications from the planetary program and earth resources activities. It is noted that the registration of existing geocoded data bases with Landsat imagery will continue to be important if the Landsat data is to be of genuine use to the user community.

Green, W. B.↗

Image registration system in the Landsat-D production environment

It is the purpose of the considered system to take pieces of imagery, called control point chips (CPC), whose geodetic location has been previously determined and stored, and locate their position in later imagery of the same area. The registration processes are carried out partially on a DEC VAX 780 computer and partially on a Floating Point Systems Array Processor. Typically sets of 20 control points are processed at a time. To process these as sets, and to optimize the use of both machines, operations are grouped into loops instead of a sequential processing for each point. Attention is given to cloud cover assessment, enhancement, correlation techniques, pixel registration, and subpixel registration.

Kiss, P.↗

AN-A46: LANDSAT scene-to-scene registration assessment

LANDSAT-4 MSS data and TM data for the 16 September 1982 scene were received. MSS data were reformatted and scene to scene registration, with previous MSS data is nearing completion. LANDSAT-2 to LANDSAT-2 MSS registration was completed. The results obtained serve as a baseline against which to compare the registrations containing LANDSAT-4 MSS. The TM data set as originally processed for the Orleans area had excessive yaw which exaggerated the forward/reverse scan pixal alignment, GSFC software was subsequently modified to minimize the problem. A detector stitching problem most pronounced in bodies of water was noted for TM channel 3 (0.63 micrometer to 0.69 micrometer).

Anderson, J. E.↗

AN-A46. LANDSAT scene-to-scene registration assessment

Initial results obtained from the registration of LANDSAT-4 MSS data to LANDSAT-2 MSS data are documented and compared with results obtained from a LANDSAT-2 MSS-to-LANDSAT-2 MSS scene-to-scene registration (using the same LANDSAT-2 MSS data as the base data set in both procedures). RMS errors calculated on the control points used in the establishment of scene-to-scene mapping equations are compared to errors computed from independently chosen verification points. Models developed to estimate actual scene-to-scene registration accuracy based on the use of electrostatic plots are also presented. Analysis or results obtained indicates a statistically significant difference in the RMS errors for the element contribution. Scan line errors were not significantly different. It appears that a modification to the LANDSAT-4 MSS scan mirror coefficients is required to correct the situation.

Anderson, J. E.↗

The use of LANDSAT-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

The MSS sensor on LANDSAT 4 is, in certain performance aspects, different from those on LANDSATS 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of LANDSAT 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using LANDSAT 4 and LANDSAT 2 data (33.35 meters) and the temporal data set constructed from two LANDSAT 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Anderson, J. E.↗

LANDSAT Scene-to-scene Registration Accuracy Assessment

Initial results obtained from the registration of LANDSAT-4 data to LANDSAT-2 MSS data are documented and compared with results obtained from a LANDSAT-2 MSS-to-LANDSAT-2 scene-to-scene registration (using the same LANDSAT-2 MSS data as the base data set in both procedures). RMS errors calculated on the control points used in the establishment of scene-to-scene mapping equations are compared to error computed from independently chosen verification points. Models developed to estimate actual scene-to-scene registration accuracy based on the use of electrostatic plots are also presented. Analysis of results indicates a statistically significant difference in the RMS errors for the element contribution. Scan line errors were not significantly different. It appears that a modification to the LANDSAT-4 MSS scan mirror coefficients is required to correct the situation.

Anderson, J. E.↗

Radar image registration and rectification

Two techniques for radar image registration and rectification are presented. In the registration method, a general 2-D polynomial transform is defined to accomplish the geometric mapping from one image into the other. The degree and coefficients of the polynomial are obtained using an a priori found tiepoint data set. In the second part of the paper, a rectification procedure is developed that models the distortion present in the radar image in terms of the radar sensor's platform parameters and the topographic variations of the imaged scene. This model, the ephemeris data and the digital topographic data are then used in rectifying the radar image. The two techniques are then used in registering and rectifying two examples of radar imagery. Each method is discussed as to its benefits, shortcomings and registration accuracy.

Naraghi, M.↗

Thematic Mapper image quality - Registration, noise, and resolution

The Landsat-4 satellite has two new imaging radiometers, including the redesigned Multispectral Scanner (MSS) and the Thematic Mapper (TM). The present investigation is concerned with an assessment of TM image quality on the basis of a study of band-to-band registration, periodic noise, and spatial resolution. In the TM images analyzed, the band-to-band registration accuracy of the instrument is very good. A few imperfections were found. Once a stable misregistration is removed, the TM should also meet its registration specifications between focal planes. Spatial resolution analyses in terms of MTF were performed in comparison modes. The forward and backward scans were shown to have virtually identical MTFs.

Wrigley, R. C.↗

Analysis of subpixel registration

The area of subpixel accuracy in image registration and edge detection was studied. Two main directions of research were pursued, edge detection and matching based on the digital geometry of edges, and random field models for probablistic analysis of registration error. In the edge detection approach, error bounds and error probabilities were computed using theoretical models. Algorithms were developed and tests on simulated imagery. The methods appear promising for high accuracy edge position estimation and registration, though further refinement of the procedures is required. Using random field models, a statistical measure of the quality of the cross correlation peak as an estimate of the offset between a sensed and a reference image was developed. Simulations were performed to determine the validity of this estimte with real imagery and to study the results of interpolating digital correlation functions to estimate the translation offset to subpixel accuracy.

Berenstein, C. A.↗

Landsat image registration - A study of system parameters

Some applications of Landsat data, particularily agricultural and forestry applications, require the ability to geometrically superimpose or register data acquired at different times and possibly by different satellites. An experimental investigation relating to a registration processor used by the Johnson Space Center for this purpose is the subject of this paper. Correlation of small subareas of images is at the heart of this registration processor and the manner in which various system parameters affect the correlation process is the prime area of investigation. Parameters investigated include preprocessing methods, methods for detecting sucessful correlations, fitting a surface to the correlation patch, fraction of pixels designated as edge pixels in edge detection adn local versus global generation of edge images. A suboptimum search procedure is used to find a good parameter set for this registration processor.

Wacker, A. G.↗

The use of Landsat-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

The MSS sensor on Landsat 4 is, in certain performance aspects, diferent from those of Landsats 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of Landsat 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using Landsat 4 and Landsat 2 data (33.35 meters) and the temporal data set constructed from two Landsat 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Anderson, J. E.↗