Training of a crater detection algorithm for Mars crater imagery
This paper discusses the use of a crater detection algorithm for Mars crater imagery.
automatic feature identification↗
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Surfaces for micrometeoroid impact crater detection
Surfaces for micrometeroid impact crater detection
Brownlee, D. E.↗
LU60645GT and MA132843GT Catalogues of Lunar and Martian Impact Craters Developed Using a Crater Shape-based Interpolation Crater Detection Algorithm for Topography Data
For Mars, 57,633 craters from the manually assembled catalogues and 72,668 additional craters identified using several crater detection algorithms (CDAs) have been merged into the MA130301GT catalogue. By contrast, for the Moon the most complete previous catalogue contains only 14,923 craters. Two recent missions provided higher-quality digital elevation maps (DEMs): SELENE (in 1/16° resolution) and Lunar Reconnaissance Orbiter (we used up to 1/512°). This was the main motivation for work on the new Crater Shape-based interpolation module, which improves previous CDA as follows: (1) it decreases the number of false-detections for the required number of true detections; (2) it improves detection capabilities for very small craters; and (3) it provides more accurate automated measurements of craters' properties. The results are: (1) LU60645GT, which is currently the most complete (up to ∼D>=8 km) catalogue of Lunar craters; and (2) MA132843GT catalogue of Martian craters complete up to ∼D>=2 km, which is the extension of the previous MA130301GT catalogue. As previously achieved for Mars, LU60645GT provides all properties that were provided by the previous Lunar catalogues, plus: (1) correlation between morphological descriptors from used catalogues; (2) correlation between manually assigned attributes and automated measurements; (3) average errors and their standard deviations for manually and automatically assigned attributes such as position coordinates, diameter, depth/diameter ratio, etc; and (4) a review of positional accuracy of used datasets. Additionally, surface dating could potentially be improved with the exhaustiveness of this new catalogue. The accompanying results are: (1) the possibility of comparing a large number of Lunar and Martian craters, of e.g. depth/diameter ratio and 2D profiles; (2) utilisation of a method for re-projection of datasets and catalogues, which is very useful for craters that are very close to poles; and (3) the extension of the previous framework for evaluation of CDAs with datasets and ground-truth catalogue for the Moon.
Craters↗
Machine Learning Based Crater Detection for Terrain Relative Navigation
As Lunar exploration continues to become more commonplace, reliable methods of precise Terrain Relative Navigation (TRN) are needed. While there are many TRN techniques available, one that has received increased interest in the past few years is that of crater based navigation. Crater based navigation has numerous benefits, including being a human recognizable feature (important for crewed missions), as well as the fact that craters are often possible hazards that need to be detected and avoided. The use of crater based navigation has been limited however. This has been due to the difficulty of running such algorithms on board a spacecraft, as well as the difficulty in procuring large amounts of the required training data. This paper presents a new rendering tool for generating large amounts of high quality training data. It then looks at two recently developed machine learning techniques for crater detection and crater identification in real-time on near-future space hardware.
computer vision↗
Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis
Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.
Image Processing; Pattern Recognition↗
Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis
Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.
Image Processing:Pattern Recognition↗
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↗
Talemzane - Algerian impact crater detected on SIR-A orbital imaging radar
In November, 1981, NASA's first Shuttle Imaging Radar mission (SIR-A) began producing maplike photographic strips of Earth scenes from orbital altitude. A Saharan radar image acquired over Algeria clearly delineates two sedimentary basins, Erg Occidental and Erg Oriental, separated by an elongated zone of exposed bedrock, the M'Zab Chebka. At the NE margin of the Chebka, rimrocks, slopes, and ejecta deposits of Talemzane meteorite impact crater appear as a distinct two km wide radar-bright ring. This unique circle of strong radar backscatter distinguishes the solitary impact structure from numerous dayas (similarly appearing karstic depressions) which characterize the region. The crater is prominent on radar, but is obscure on optically obtained satellite and aircraft images, as are partly buried fluvial drainage systems and fault-block traces developed in bedrocks of the Chebka. Radar detection of an annular drainage system indicates possible presence of a ring graben at the crater. Brightest radar signals on the image are cultural features at recently developed gas fields near Hassi er R'Mel.
Mchone, John F.↗
Unsupervised Detection of Planetary Craters by a Marked Point Process
With the launch of several planetary missions in the last decade, a large amount of planetary images is being acquired. Preferably, automatic and robust processing techniques need to be used for data analysis because of the huge amount of the acquired data. Here, the aim is to achieve a robust and general methodology for crater detection. A novel technique based on a marked point process is proposed. First, the contours in the image are extracted. The object boundaries are modeled as a configuration of an unknown number of random ellipses, i.e., the contour image is considered as a realization of a marked point process. Then, an energy function is defined, containing both an a priori energy and a likelihood term. The global minimum of this function is estimated by using reversible jump Monte-Carlo Markov chain dynamics and a simulated annealing scheme. The main idea behind marked point processes is to model objects within a stochastic framework: Marked point processes represent a very promising current approach in the stochastic image modeling and provide a powerful and methodologically rigorous framework to efficiently map and detect objects and structures in an image with an excellent robustness to noise. The proposed method for crater detection has several feasible applications. One such application area is image registration by matching the extracted features.
Troglio, G.↗
Optical landmark detection for spacecraft navigation
In this paper, a new crater detection algorithm is suggested. Experimental studies show that this new algorithm can achieve sub-pixel accuracy in position, its detection rate is better than 90% and its false alarm rate is less than 5%. These good characteristics indicate that it is an ideal crater detection algorithm for spacecraft optical navigation.
optical↗
Automated detection of craters and other geological features
We report on our effort to develop algorithms to detect, size, and classify geological features in planetary and asteroidal data sets.
object recognition data understanding scalability ↗
Processing Images of Craters for Spacecraft Navigation
A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.
Cheng, Yang↗
NASA’s Moon Trek Portal: New Capabilities Supporting Mission Planning and Engagement
Introduction: NASA’s Moon Trek (https://trek.nasa.gov/moon/) is one of a growing number of interactive, browser-based, online portals for planetary data visualization and analysis produced by NASA’s Solar System Treks Project (SSTP). Moon Trek continues to be enhanced with new data and new capabilities enabling it to facilitate the planning and conducting of upcoming lunar missions by NASA, its commercial partners, and its international partners, as well as advancing its role as a valuable outreach tool. A Comprehensive Online Web Portal: Developed at NASA’s Jet Propulsion Laboratory (JPL) and managed as a project of NASA’s Solar System Exploration Research Virtual Institute (SSERVI) at NASA Ames Research Center, Moon Trek is a browser-based web portal. The portal provides easy-to-use tools for browsing, data layering, data product blending, and feature search among thousands of data products covering topography, mineralogy, elemental abundance, geology, and much more. Visualizations are provided in var-ious map projections, interactive 3D viewing, and in virtual reality. Using an in-house stereo workflow, SSTP is able to produce new NAC-based high-resolution mosaics and DEMs. Diverse Applications for Lunar Exploration: Baseline analytic tools available to all users include dis-tance measurement, elevation profiling, sun angle calculation, and 3D print file generation. More advanced account-level tools allow users to perform more computationally intensive analyses. These include ray-traced lighting analysis for user-specified areas over user-specified time/date ranges and time intervals, electro-static surface potential analysis, subsetting of large data products, slope analysis, and Lunar Laser Ranging geometry calculation. Artificial intelligence (AI) and ma-chine learning (ML) based tools have been implemented for crater detection and hazard analysis, boulder detection and hazard analysis, and rockfall detection. New Tools Facilitating Exploration: Additional, new tools have recently been added and others are in development, offering even greater functionality in con-ducting analyses of potential landing sites and areas of surface operations. The new Line-of-Sight tool facilitates communications planning between locations on the lunar surface, between any given site on the lunar surface and a specified ground station on the Earth, and between a site on the lunar surface and a relay asset in lunar orbit, all taking into account local lunar topography. The new Data Plotter tool provides both tabular and graphical representations of pixel values along a user specified path for a growing number of data products. The new NAC Finder tool will identify and pro-vide access to NAC images that intersect a user-defined path or bounded area. The SSTP development team is looking to leverage the capabilities of its existing AI and ML crater, boulder, and rockfall detection and analysis tools, and extend that technology to a generalized feature detector that can be trained on instances of specific types of landforms and then search the lunar surface for more examples of such features. New traverse planning tools are being developed with use cases in generalized concept studies and specific mission planning in mind. These will facilitate finding optimal traverse paths based on constraints such as slope, lighting, hazard avoidance, and communications. These will be complemented by new traverse visualization capabilities. Users will be able to interactively ride along with a rover, examining 3D views of the terrain while adjusting camera height and viewing angle along with selecting different data layer overlays to drape across the terrain. Engaging the Public: The capabilities being developed for mission planning are being leveraged to further enhance Moon Trek’s proven utility as a valuable public outreach resource. This includes providing multiple lev-els of engagement with different points of entry. At its simplest level, promoting understanding through visualization, media and the public will be able to easily visualize and conduct their own exploration of lunar sites targeted by NASA and its partners. For a more in-depth experience, we are working with our stakeholders to promote understanding through interaction by extend-ing our current landing site and traverse analysis capabilities, making simplified access to these tools available to those who want to explore more deeply key factors in planning a mission through interactive and possibly even gamified experiences. The highest degree of public outreach, focusing on engagement through scientific participation, could be achieved through our work with missions and the NASA Office of the Chief Scientist on Moon Trek’s extension as a tool with specialized capabilities for facilitating citizen science. In such scenarios, participants become members of extended mis-sion science teams, using dedicated and integrated interfaces to analyze mission data to help answer questions key to lunar science and exploration. We are work-ing with NASA’s Office of Communications, museums, planetariums, and the media to help them easily integrate accurate, detailed visualizations of NASA’s lunar destinations and exploration into their content/productions and to engage diverse audiences in diverse venues.
Moon Trek↗
Implementation of Machine Learning Methods for Crater-Based Navigation
Terrain Relative Navigation methods require surface feature detectors to gain information from images used to improve on-board state estimates. This paper presents the development of a crater detection method based on Machine Learning that can extract data from optical images with different crater shapes and sizes, under varying lighting conditions. This work includes an automated capability for generating labeled training data and iterative testing of the neural network-based crater detector. Preliminary results are included to quantify the detector’s accuracy compared to a known crater catalog, given a set of real lunar images from the Lunar Reconnaissance Orbiter.
Sofia G Catalan↗
Large Impact Features on Europa: Results of the Galileo Nominal Mission
The Galileo Orbiter examined several impact features on Europa at considerably better resolution than was possible from Voyager. The new data allow us to describe the morphology and infer the geology of the largest impact features on Europa, which are probes into the crust. We observe two basic types of large impact features: (1) "classic" impact craters that grossly resemble well-preserved lunar craters of similar size but are more topographically subdued (e.g., Pwyll) and (2) very flat circular features that lack the basic topographic structures of impact craters such as raised rims, a central depression, or central peaks, and which largely owe their identification as impact features to the field of secondary craters radially sprayed about them (e.g., Callanish). Our interpretation is that the classic craters (all <30 km diameter) formed entirely within a solid target at least 5 to 10 km thick that exhibited brittle behavior on time scales of the impact events. Some of the classic craters have a more subdued topography than fresh craters of similar size on other icy bodies such as Ganymede and Callisto, probably due to the enhanced viscous relaxation produced by a steeper thermal gradient on Europa. Pedestal ejecta facies on Europa (and Ganymede) may be produced by the relief-flattening movement of plastically deforming but otherwise solid ice that was warm at the time of emplacement. Callanish and Tyre do not appear to be larger and even more viscously relaxed versions of the classic craters; rather they display totally different morphologies such as distinctive textures and a series of large concentric structural rings cutting impact-feature-related materials. Impact simulations suggest that the distinctive morphologies would not be produced by impact into a solid ice target, but may be explained by impact into an ice layer approximately 10 to 15 km thick overlying a low-viscosity material such as water. The very wide (near antipodal) separation of Callanish and Tyre imply that approximately 10-15 km may have been the global average thickness of the rigid crust of Europa when these impacts occurred. The absence of detectable craters superposed on the interior deposits of Callanish suggests that it is geologically young (< 10(exp 8) years). Hence, it seems likely that our preliminary conclusions about the subsurface structure of Europa apply to the current day.
Moore, Jeffrey M.↗
Lunar surface: Changes in 31 months and micrometeoroid flux
A preliminary comparison of Surveyor 3 and Apollo 12 photographs of areas disturbed by the Surveyor is described. About 60 Surveyor pictures taken in April and May 1967 and 20 Apollo photographs including stereo pairs were examined in detail. Only one definite change in the surface, other than those produced by astronauts, was noted. This is a particle about 2 mm in diameter which appears in the Apollo photographs of a Surveyor footpad imprint but which does not appear in the Surveyor photographs. The walls made by Surveyor footpads and surface sampler were still in place, and surface areas darkened by ejected fines during the Surveyor landing still appeared dark. The absence of detectable craters in the footpad imprint implies a very low micrometeorite flux on the lunar surface.
Jaffe, L. D.↗
Autonomous landmark tracking orbit determination strategy
In this paper, an orbit determination strategy is described that is fully autonomous and relies on a computer-based crater detection and identification algorithm that is suitable for both automation of the ground based navigation system and autonomous spacecraft based navigation.
landmark tracking orbit determination↗