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Journal articles on the topic 'Lunar images'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Korokhin, Viktor V., Yuri I. Velikodsky, Eugene V. Shalygin, Yuriy G. Shkuratov, Vadym G. Kaydash, and Gorden Videen. "Retrieving lunar topography from multispectral LROC images." Planetary and Space Science 92 (March 2014): 65–76. http://dx.doi.org/10.1016/j.pss.2014.01.008.

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2

Oberst, J., M. Waehlisch, A. C. Cook, T. Roatsch, and R. Jaumann. "Lunar details gleaned from digital stereo images." Eos, Transactions American Geophysical Union 78, no. 41 (1997): 445. http://dx.doi.org/10.1029/97eo00275.

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3

Balcerak, Ernie. "Lunar images alter understanding of impact history." Eos, Transactions American Geophysical Union 93, no. 6 (February 7, 2012): 64. http://dx.doi.org/10.1029/2012eo060012.

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4

Elaksher, Ahmed F., Ahmad Al-Jarrah, and Kyle Walker. "Lunar Surface Reconstruction from Apollo MC Images." Earth, Moon, and Planets 115, no. 1-4 (April 26, 2015): 71–82. http://dx.doi.org/10.1007/s11038-015-9468-8.

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5

Di, K., B. Xu, B. Liu, M. Jia, and Z. Liu. "GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 13, 2016): 369–74. http://dx.doi.org/10.5194/isprsarchives-xli-b4-369-2016.

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This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang’e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

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Di, K., B. Xu, B. Liu, M. Jia, and Z. Liu. "GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 13, 2016): 369–74. http://dx.doi.org/10.5194/isprs-archives-xli-b4-369-2016.

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This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang’e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

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7

Di, K., J. Oberst, I. Karachevtseva, and B. Wu. "TOPOGRAPHIC MAPPING OF THE MOON IN THE 21ST CENTURY: FROM HECTOMETER TO MILLIMETER SCALES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 1117–24. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1117-2020.

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Abstract. This paper presents a review of lunar topographic mapping in the two decades of the 21st century, including descriptions of lunar exploration missions, relevant payloads and data, mapping techniques, as well as global and regional mapping products. Various lunar photogrammetric mapping techniques such as construction of geometric models of lunar orbital images, block adjustments, shape from shading, co-registration of lunar orbital image and elevation data have been developed to process lunar orbital images and generate mapping products. Global topographic products at hectometer and decameter scales have been produced from orbital images and/or laser altimeter data. Regional topographic maps of the landing sites and other sites of interest have been generated at meter-scale using the sub-meter to meter resolution orbital images. Detailed local topographic products at centimeter to millimeter scales of the landing sites and rover traverse areas have been produced using descent images acquired by the landers and stereo images acquired by the rovers. These multiple-scale topographic mapping products have been extensively used to support various science applications, as well as engineering applications such as surface operations of the rovers.

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8

Su, Qing Hua, Yan Zhao, Kui Yang, and Shao Chen Zhang. "Automatic Analysis of Mineral’s Abundance." Advanced Materials Research 765-767 (September 2013): 2369–73. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.2369.

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The mineral is the important data in the Lunar Exploration. The main objective of this work is to segmentation lunar craters with the C-V Model, and to quantify the images terrain and the abundance of lunar surface minerals based on Crater distribution law and Soil Characterization Consortium data set with Hapke model and lunar surface reflectance. Actual lunar images of mare region as an example, this method analysis result of the minerals abundance are basically same with published literature. This method can be simple rapid in-time implemented in real-time lunar exploration.

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9

Liu, Bin, Mengna Jia, Kaichang Di, Jürgen Oberst, Bin Xu, and Wenhui Wan. "Geopositioning precision analysis of multiple image triangulation using LROC NAC lunar images." Planetary and Space Science 162 (November 2018): 20–30. http://dx.doi.org/10.1016/j.pss.2017.07.016.

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10

Anthony Thomas, Digina Derose, Sahaya Cyril, and Smita Dange. "Intelligent Lunar Landing Site Recommender." International Journal of Engineering and Management Research 11, no. 2 (April 30, 2021): 184–88. http://dx.doi.org/10.31033/ijemr.11.2.26.

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Space exploration is brewing to be one of the most sought after fields in today’s world with each country pooling in resources and skilled minds to be one step ahead of the other. The core aspect of space exploration is exoplanet exploration, i.e., by sending unmanned rovers or manned spaceships to planets and celestial bodies within and beyond our solar system to determine habitable planets. Landscape inspection and traversal is the core feature of any planetary exploration mission. It is often a strenuous task to carry out a machine learning experiment on an extraterrestrial surface like the Moon. Consequent lunar explorations undertaken by various space agencies in the last four decades have helped to analyze the nature of the Lunar Terrain through satellite images. The motion of the rovers has traditionally been governed by the use of sensors that achieve obstacle avoidance. In this project we aim to detect craters on the lunar landscape which in turn will be used to determine soft landing sites on the lunar landscape for exploring the terrain, based on the classified lunar landscape images.

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11

Speyerer, E. J., R. V. Wagner, and M. S. Robinson. "GEOMETRIC CALIBRATION OF THE CLEMENTINE UVVIS CAMERA USING IMAGES ACQUIRED BY THE LUNAR RECONNAISSANCE ORBITER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 497–501. http://dx.doi.org/10.5194/isprsarchives-xli-b4-497-2016.

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The Clementine UVVIS camera returned over half a million images while in orbit around the Moon in 1994. Since the Clementine mission, our knowledge of lunar topography, gravity, and the location of features on the surface has vastly improved with the success of the Gravity Recovery and Interior Laboratory (GRAIL) mission and ongoing Lunar Reconnaissance Orbiter (LRO) mission. In particular, the Lunar Reconnaissance Orbiter Camera (LROC) has returned over a million images of the Moon since entering orbit in 2009. With the aid of improved ephemeris and on-orbit calibration, the LROC team created a series of precise and accurate global maps. With the updated reference frame, older lunar maps, such as those generated from Clementine UVVIS images, are misaligned making cross-mission analysis difficult. In this study, we use feature-based matching routines to refine and recalibrate the interior and exterior orientation parameters of the Clementine UVVIS camera. After applying these updates and rigorous orthorectification, we are able generate precise and accurate maps from UVVIS images to help support lunar science and future cross-mission investigations.

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12

Speyerer, E. J., R. V. Wagner, and M. S. Robinson. "GEOMETRIC CALIBRATION OF THE CLEMENTINE UVVIS CAMERA USING IMAGES ACQUIRED BY THE LUNAR RECONNAISSANCE ORBITER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 497–501. http://dx.doi.org/10.5194/isprs-archives-xli-b4-497-2016.

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The Clementine UVVIS camera returned over half a million images while in orbit around the Moon in 1994. Since the Clementine mission, our knowledge of lunar topography, gravity, and the location of features on the surface has vastly improved with the success of the Gravity Recovery and Interior Laboratory (GRAIL) mission and ongoing Lunar Reconnaissance Orbiter (LRO) mission. In particular, the Lunar Reconnaissance Orbiter Camera (LROC) has returned over a million images of the Moon since entering orbit in 2009. With the aid of improved ephemeris and on-orbit calibration, the LROC team created a series of precise and accurate global maps. With the updated reference frame, older lunar maps, such as those generated from Clementine UVVIS images, are misaligned making cross-mission analysis difficult. In this study, we use feature-based matching routines to refine and recalibrate the interior and exterior orientation parameters of the Clementine UVVIS camera. After applying these updates and rigorous orthorectification, we are able generate precise and accurate maps from UVVIS images to help support lunar science and future cross-mission investigations.

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13

Bart, Gwendolyn D., Ryan D. Nickerson, Matthew T. Lawder, and H. J. Melosh. "Global survey of lunar regolith depths from LROC images." Icarus 215, no. 2 (October 2011): 485–90. http://dx.doi.org/10.1016/j.icarus.2011.07.017.

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14

Buratti, B. "Lunar Transient Phenomena: What Do the Clementine Images Reveal?" Icarus 146, no. 1 (July 2000): 98–117. http://dx.doi.org/10.1006/icar.2000.6373.

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15

Gao, Hongwei, Yuqi Zhou, Yueqiu Jiang, Jiahui Yu, Zhaojie Ju, and Jinguo Liu. "Measurement of Simulated Lunar Soil Information Using Rutting Images." IEEE Access 8 (2020): 130281–92. http://dx.doi.org/10.1109/access.2020.3006460.

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16

Micheal, Anto A., K. Vani, and S. Sanjeevi. "Automatic Graben Detection in Lunar Images Using Hessian Technique." Journal of the Indian Society of Remote Sensing 42, no. 2 (December 10, 2013): 445–51. http://dx.doi.org/10.1007/s12524-013-0316-x.

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17

Vijayan, S., K. Vani, and S. Sanjeevi. "Topographical analysis of lunar impact craters using SELENE images." Advances in Space Research 52, no. 7 (October 2013): 1221–36. http://dx.doi.org/10.1016/j.asr.2013.06.025.

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18

Gao, Yang, Conrad Spiteri, Chun-Lai Li, and Yong-Chun Zheng. "Lunar soil strength estimation based on Chang’E-3 images." Advances in Space Research 58, no. 9 (November 2016): 1893–99. http://dx.doi.org/10.1016/j.asr.2016.07.017.

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19

Peng, Man, Kaichang Di, Yexin Wang, Wenhui Wan, Zhaoqin Liu, Jia Wang, and Lichun Li. "A Photogrammetric-Photometric Stereo Method for High-Resolution Lunar Topographic Mapping Using Yutu-2 Rover Images." Remote Sensing 13, no. 15 (July 28, 2021): 2975. http://dx.doi.org/10.3390/rs13152975.

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Topographic products are important for mission operations and scientific research in lunar exploration. In a lunar rover mission, high-resolution digital elevation models are typically generated at waypoints by photogrammetry methods based on rover stereo images acquired by stereo cameras. In case stereo images are not available, the stereo-photogrammetric method will not be applicable. Alternatively, photometric stereo method can recover topographic information with pixel-level resolution from three or more images, which are acquired by one camera under the same viewing geometry with different illumination conditions. In this research, we extend the concept of photometric stereo to photogrammetric-photometric stereo by incorporating collinearity equations into imaging irradiance model. The proposed photogrammetric-photometric stereo algorithm for surface construction involves three steps. First, the terrain normal vector in object space is derived from collinearity equations, and image irradiance equation for close-range topographic mapping is determined. Second, based on image irradiance equations of multiple images, the height gradients in image space can be solved. Finally, the height map is reconstructed through global least-squares surface reconstruction with spectral regularization. Experiments were carried out using simulated lunar rover images and actual lunar rover images acquired by Yutu-2 rover of Chang’e-4 mission. The results indicate that the proposed method achieves high-resolution and high-precision surface reconstruction, and outperforms the traditional photometric stereo methods. The proposed method is valuable for ground-based lunar surface reconstruction and can be applicable to surface reconstruction of Earth and other planets.

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20

Saxena, Jag Mohan, H. M. Saxena, and Priyanka Saxena. "THE LOST INDIAN CHANDRAYAAN 2 LANDER VIKRAM AND ROVER PRAGYAAN FOUND INTACT IN SINGLE PIECE ON THE MOON." International Journal of Research -GRANTHAALAYAH 8, no. 12 (December 29, 2020): 103–9. http://dx.doi.org/10.29121/granthaalayah.v8.i12.2020.2608.

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The Lunar Lander Vikram of the Moon Mission Chandrayaan 2 of the Indian Space Research Organization (ISRO) lost communication with the Lunar Orbiter and the mission control nearly 2.1 kms above the lunar surface during its landing on the Moon on 7th September, 2019. The exact location and the sight of the lost lander and rover are still elusive. We present here the exact location and first images of the lander Vikram and rover Pragyaan sighted on the lunar surface. It is evident from the processed images that the lander was intact and in single piece on landing away from the scheduled site and its ramp was deployed to successfully release the rover Pragyan on to the lunar surface. This contradicts earlier reports that the lander was disintegrated into small pieces and debris which were scattered far away from the proposed landing site.

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21

Makeyev, A. B., and N. I. Bryanchaninova. "Typomorphism of rock-forming minerals of Lunar regolith, Luna-16, -20, -24: comparision of sea vs continent vs sea." Georesursy 23, no. 1 (March 30, 2021): 94–105. http://dx.doi.org/10.18599/grs.2021.1.10.

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The study focuses on the comparison of the chemical and mineral composition of Lunar regolith probes from Luna-16, -20, -24 stations and their the sea-continent environments. Using microprobe JXA-8200 and JSM-5610LV (400 analyses, 50 images, 9 fragments of layer-by-layer core samples) 18 mineral phases and their 12 varieties were diagnosed. The most common are iron-magnesium and calcium-bearing varieties of silicates – anortite, clinopyroxenes and olivine. The typomorphic features of rock-forming minerals in two types of the lunar surface are discussed. The composition of chromespinelids is demonstrated on a triangular prism diagram.

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22

Wang, Yang, Xiuqing Hu, Lin Chen, Yu Huang, Zhanfeng Li, Shurong Wang, Peng Zhang, Ronghua Wu, Lu Zhang, and Wei Wang. "Comparison of the Lunar Models Using the Hyper-Spectral Imager Observations in Lijiang, China." Remote Sensing 12, no. 11 (June 10, 2020): 1878. http://dx.doi.org/10.3390/rs12111878.

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A lunar observation campaign was conducted using a hyper-spectral imaging spectrometer in Lijiang, China from December 2015 to February 2016. The lunar hyper-spectral images in the visible to near-infrared region (VNIR) have been obtained in different lunar phases with absolute scale established by the National Institute of Metrology (NIM), China using the lamp–plate calibration system. At the same time, the aerosol optical depth (AOD) is measured regularly by a lidar and a lunar CE318U for atmospheric characterization to provide nightly atmosphere extinction correction of lunar observations. This paper addressed the complicated data processing procedure in detail from raw images of the spectrometer into the spectral lunar irradiance in different lunar phases. The result of measurement shows that the imaging spectrometer can provide lunar irradiance with uncertainties less than 3.30% except for absorption bands. Except for strong atmosphere absorption region, the mean spectral irradiance difference between the measured irradiance and the ROLO (Robotic Lunar Observatory) model is 8.6 ± 2% over the course of the lunar observation mission. The ROLO model performs more reliable to clarify absolute and relative accuracy of lunar irradiance than that of the MT2009 model in different Sun–Moon–Earth geometry. The spectral ratio analysis of lunar irradiance shows that band-to-band variability in the ROLO model is consistent within 2%, and the consistency of the models in the lunar phase and spectrum is well analyzed and evaluated from phase dependence and phase reddening analysis respectively.

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23

Micheal, Anto A., and K. Vani. "Clustering-based dome detection in lunar images using DTM data." International Journal of Remote Sensing 39, no. 18 (November 24, 2017): 5794–808. http://dx.doi.org/10.1080/01431161.2017.1402388.

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24

Chen, Hui-Zhong, Ning Jing, Jun Wang, Yong-Guang Chen, and Luo Chen. "A Novel Saliency Detection Method for Lunar Remote Sensing Images." IEEE Geoscience and Remote Sensing Letters 11, no. 1 (January 2014): 24–28. http://dx.doi.org/10.1109/lgrs.2013.2244845.

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25

Tamililakkiya, V. "Linear and Non-Linear Feature Extraction Algorithms for Lunar Images." Signal & Image Processing : An International Journal 2, no. 4 (December 31, 2011): 161–72. http://dx.doi.org/10.5121/sipij.2011.2414.

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26

Wu, Ronghua, Peng Zhang, Na Xu, Xiuqing Hu, Lin Chen, Lu Zhang, and Zhongdong Yang. "FY-3D MERSI On-Orbit Radiometric Calibration from the Lunar View." Sensors 20, no. 17 (August 20, 2020): 4690. http://dx.doi.org/10.3390/s20174690.

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Limited by the on-orbital calibration capability, scaling the measured radiance in accuracy and stability is challenging for the Earth observation satellites in the reflective solar bands (RSBs). Although the lunar calibration is a well-developed technique in the RSBs, limited work has been done for Chinese Earth observation satellites. To improve the on-orbital calibration performance, the advanced MEdium Resolution Spectral Imager (MERSI II), which is the primary payload of the fourth satellite of the Fengyun 3 Series (FY-3D), expands the space view angle of the imager in order to capture better lunar images. In this study, we propose an absolute radiometric calibration method based on the FY-3D/MERSI lunar observation data. A lunar irradiance model named ROLO/GIRO has been used together with the necessary data procedures, including dark current count estimation, single pixel irradiance calculation, and full disk lunar irradiance calculation. The calibration coefficients obtained by the lunar calibration are compared with the pre-launch laboratory calibration. The results show that the deviations between the two calibration procedures are in a reasonable range in general. However, a relatively high non-linear response was found in the low energy incidence for some detectors, which leads to the large deviation in the corresponding bands. This study explored an ideal and independent method to validate MERSI on-orbit radiometric performance. The lunar calibration practiced for MERSI also gave a valuable example that can be recommended to the other Chinese Earth observation satellites.

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27

Yang, Z., and Z. Kang. "ACCURATE REGISTRATION OF THE CHANG’E-1 IIM DATA BASED ON LRO LROC-WAC MOSICA DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W1 (July 25, 2017): 191–98. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w1-191-2017.

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In the detection of the moon, the visible and near-infrared reflectance data of the lunar material are important information sources for lunar chemical substances and mineral inversion. The Interferometer Imaging Spectrometer (IIM) aboard the Chang'E-1 lunar orbiter is the first multispectral imaging spectrometer for Chinese lunar missions. In this paper, we use the mosaic image of global moon acquired by the Wide-angle Camera (WAC) of the Lunar Reconnaissance Orbiter Camera (LROC) to realize the accurate registration of Chang'E-1 IIM hyperspectral images. Due to the lack of GCPs, the emphasis of this work is to find a huge number of homologous points. The method proposed in this paper is to obtain several homologous points by manually matching, and then we utilize those points to calculate the initial homography matrix of LROC-WAC image and IIM image. This matrix is used to predict the area on IIM image where homologous points may be located, and the locations of the homologous points are determined by the orientation correlation in frequency domain. Finally we save the parts of homologous points which satisfied the conversion relationship of initial homography matrix to calculate homography matrix again. We use this iterative way to obtain a more accurate location of the homologous points. In this process, we take into account that the geometric deformations of different regions on IIM image are quite different. Therefore, we added image threshold segmentation based on the initial homography matrix in the experiment, and completed the above work of finding the homologous points on the segmented images. The final realization of registration accuracy of IIM images are in 1&ndash;2 pixels (RMSE). This provides a reliable data assurance for the subsequent study of using IIM images to inverse the lunar elements.

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28

Di, K., B. Liu, M. Peng, X. Xin, M. Jia, W. Zuo, J. Ping, B. Wu, and J. Oberst. "AN INITIATIVE FOR CONSTRUCTION OF NEW-GENERATION LUNAR GLOBAL CONTROL NETWORK USING MULTI-MISSION DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W1 (July 25, 2017): 29–34. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w1-29-2017.

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A lunar global control network provides geodetic datum and control points for mapping of the lunar surface. The widely used Unified Lunar Control Network 2005 (ULCN2005) was built based on a combined photogrammetric solution of Clementine images acquired in 1994 and earlier photographic data. In this research, we propose an initiative for construction of a new-generation lunar global control network using multi-mission data newly acquired in the 21<sup>st</sup> century, which have much better resolution and precision than the old data acquired in the last century. The new control network will be based on a combined photogrammetric solution of an extended global image and laser altimetry network. The five lunar laser ranging retro-reflectors, which can be identified in LROC NAC images and have cm level 3D position accuracy, will be used as absolute control points in the least squares photogrammetric adjustment. Recently, a new radio total phase ranging method has been developed and used for high-precision positioning of Chang’e-3 lander; this shall offer a new absolute control point. Systematic methods and key techniques will be developed or enhanced, including rigorous and generic geometric modeling of orbital images, multi-scale feature extraction and matching among heterogeneous multi-mission remote sensing data, optimal selection of images at areas of multiple image coverages, and large-scale adjustment computation, etc. Based on the high-resolution new datasets and developed new techniques, the new generation of global control network is expected to have much higher accuracy and point density than the ULCN2005.

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29

Ye, L., M. Peng, K. Di, B. Liu, and Y. Wang. "LUNAR TERRAIN RECONSTRUCTION FROM MULTI-VIEW LROC NAC IMAGES BASED ON SEMI-GLOBAL MATCHING IN OBJECT SPACE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 1177–83. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1177-2020.

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Abstract. Most of the lunar surface area has been observed from different viewing conditions thanks to the on-orbit work of lunar orbiters, a large amount of images are available for photogrammetric three-dimensional mapping, which is an important issue for lunar exploration. Theoretically, multi-view images contain more information than a single stereo pair and can get better 3D mapping results. In this paper, the semi-global matching method is applied to the object space, and the steps of cost calculation, cost aggregation, and elevation calculation are performed to obtain the three-dimensional coordinates directly. Compared with the traditional image-based semi-global matching method, the object-based semi-global method is more easily extended to multi-view images, which is beneficial for applying multi-view image information. In addition, it does not require steps such as stereo rectification and forward intersection, that is, the overall pipeline is more elegant. Using the LRO NAC images covering Apollo 11 landing area as the experimental data, the result shows that the object-based semi-global matching is competent for the multi-view image matching and the multi-view image result achieves higher accuracy and more details than the single stereo pair. Furthermore, the experimental results of Zhinyu crater data show that this method can also alleviate the uncertainty of the lunar orbiter's positioning to some extent.

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30

Lawson, Stefanie L., and Bruce M. Jakosky. "Lunar surface thermophysical properties derived from Clementine LWIR and UVVIS images." Journal of Geophysical Research: Planets 106, E11 (November 1, 2001): 27911–32. http://dx.doi.org/10.1029/2000je001391.

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31

Yan, Ruicheng, Zhiguo Cao, Jianhu Wang, Sheng Zhong, Dominik Klein, and Armin Cremers. "Horizontal velocity estimation via downward looking descent images for lunar landing." IEEE Transactions on Aerospace and Electronic Systems 50, no. 2 (April 2014): 1197–221. http://dx.doi.org/10.1109/taes.2014.120065.

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32

Wang, Wei, Wenbin Zhao, and Zhengxu Zhao. "Research on Terrain Reconstruction of Twin Sequence Images in Lunar Exploration." International Journal of Signal Processing, Image Processing and Pattern Recognition 7, no. 5 (October 31, 2014): 401–8. http://dx.doi.org/10.14257/ijsip.2014.7.5.34.

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33

Micheal, Anto A., and K. Vani. "Automatic mountain detection in lunar images using texture of DTM data." Computers & Geosciences 82 (September 2015): 130–38. http://dx.doi.org/10.1016/j.cageo.2015.06.008.

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34

Wang, J., J. Li, S. Wang, T. Yu, Z. Rong, X. He, Y. You, et al. "COMPUTER VISION IN THE TELEOPERATION OF THE YUTU-2 ROVER." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2020 (August 3, 2020): 595–602. http://dx.doi.org/10.5194/isprs-annals-v-3-2020-595-2020.

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Abstract. On January 3, 2019, the Chang'e-4 (CE-4) probe successfully landed in the Von Kármán crater inside the South Pole-Aitken (SPA) basin. With the support of a relay communication satellite "Queqiao" launched in 2018 and located at the Earth-Moon L2 liberation point, the lander and the Yutu-2 rover carried out in-situ exploration and patrol surveys, respectively, and were able to make a series of important scientific discoveries. Owing to the complexity and unpredictability of the lunar surface, teleoperation has become the most important control method for the operation of the rover. Computer vision is an important technology to support the teleoperation of the rover. During the powered descent stage and lunar surface exploration, teleoperation based on computer vision can effectively overcome many technical challenges, such as fast positioning of the landing point, high-resolution seamless mapping of the landing site, localization of the rover in the complex environment on the lunar surface, terrain reconstruction, and path planning. All these processes helped achieve the first soft landing, roving, and in-situ exploration on the lunar farside. This paper presents a high-precision positioning technology and positioning results of the landing point based on multi-source data, including orbital images and CE-4 descent images. The method and its results have been successfully applied in an actual engineering mission for the first time in China, providing important support for the topographical analysis of the landing site and mission planning for subsequent teleoperations. After landing, a 0.03 m resolution DOM was generated using the descent images and was used as one of the base maps for the overall rover path planning. Before each movement, the Yutu-2 rover controlled its hazard avoidance cameras (Hazcam), navigation cameras (Navcam), and panoramic cameras (Pancam) to capture stereo images of the lunar surface at different angles. Local digital elevation models (DEMs) with a 0.02 m resolution were routinely produced at each waypoint using the Navcam and Hazcam images. These DEMs were then used to design an obstacle recognition method and establish a model for calculating the slope, aspect, roughness, and visibility. Finally, in combination with the Yutu-2 rover mobility characteristics, a comprehensive cost map for path search was generated.By the end of the first 12 lunar days, the Yutu-2 rover has been working on the lunar farside for more than 300 days, greatly exceeding the projected service life. The rover was able to overcome the complex terrain on the lunar farside, and travelled a total distance of more than 300 m, achieving the "double three hundred" breakthrough. In future manned lunar landing and exploration of Mars by China, computer vision will play an integral role to support science target selection and scientific investigations, and will become an extremely important core technology for various engineering tasks.

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Kang, Zhizhong, Xingkun Wang, Teng Hu, and Juntao Yang. "Coarse-to-Fine Extraction of Small-Scale Lunar Impact Craters From the CCD Images of the Chang’E Lunar Orbiters." IEEE Transactions on Geoscience and Remote Sensing 57, no. 1 (January 2019): 181–93. http://dx.doi.org/10.1109/tgrs.2018.2852717.

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Wan, W., Z. Liu, Y. Wang, M. Peng, K. Di, C. Liu, L. Li, et al. "TOPOGRAPHIC MAPPING WITH MANIPULATOR ARM CAMERA IN LUNAR SAMPLE RETURN MISSION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 1159–63. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1159-2020.

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Abstract. The topographic mapping of sampling areas, providing basic sampling environment information, is crucial in sample return mission. The fixed monitoring cameras were designed for mapping of sampling areas in fixed effective resolution. In order to perform more detailed topographic analysis of sampling areas, this paper proposed a topographic mapping method based on the sequential sample images captured with the movements of manipulator arm. The tie point matching results and the image exterior orientation parameters obtained from measurements of manipulator arm joints were employed to the weighted bundle adjustment based optimization for the accurate topographic mapping. The simulated images were adopted to validate the effectiveness and accuracy of the proposed method.

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Li, Hui, and Cheng Zhong. "A machine vision based autonomous navigation system for Lunar rover: the model and key technique." Sensor Review 36, no. 4 (September 19, 2016): 377–85. http://dx.doi.org/10.1108/sr-01-2016-0001.

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Purpose This study aims to find a feasible precise navigation model for the planed Lunar rover. Autonomous navigation is one of the most important missions in the Chinese Lunar exploration project. Machine vision is expected to be a promising option for this mission because of the dramatic development of an image processing technique. However, existing attempts are often subject to low accuracy and errors accumulation. Design/methodology/approach In this paper, a novel autonomous navigation model was developed, based on the rigid geometric and photogrammetric theory, including stereo perception, relative positioning and absolute adjustment. The first step was planned to detect accurate three-dimensional (3D) surroundings around the rover by matching stereo-paired images; the second was used to decide the local location and orientation changes of the rover by matching adjacent images; and the third was adopted to find the rover’s location in the whole scene by matching ground image with satellite image. Among them, the SURF algorithm that had been commonly believed as the best algorithm for matching images was adopted to find matched images. Findings Experiments indicated that the accurate 3D scene, relative positioning and absolute adjustment were easily generated and illustrated with the matching results. More importantly, the proposed algorithm is able to match images with great differences in illumination, scale and observation angle. All experiments and findings in this study proved that the proposed method could be an alternative navigation model for the planed Lunar rover. Originality/value With the matching results, an accurate 3D scene, relative positioning and absolute adjustment of rover can be easily generated. The whole test proves that the proposed method could be a feasible navigation model for the planed Lunar rover.

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Mahanti, P., M. S. Robinson, H. Sato, A. Awumah, and M. Henriksen. "ENHANCEMENT OF SPATIAL RESOLUTION OF THE LROC WIDE ANGLE CAMERA IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 685–92. http://dx.doi.org/10.5194/isprsarchives-xli-b7-685-2016.

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Image fusion, a popular method for resolution enhancement in Earth-based remote sensing studies involves the integration of geometric (sharpness) detail of a high-resolution panchromatic (Pan) image and the spectral information of a lower resolution multi-spectral (MS) image. Image fusion with planetary images is not as widespread as with terrestrial studies, although successful application of image fusion can lead to the generation of higher resolution MS image data. A comprehensive comparison of six image fusion algorithms in the context of lunar images is presented in this work. Performance of these algorithms is compared by visual inspection of the high-resolution multi-spectral products, derived products such as band-to-band ratio and composite images, and performance metrics with an emphasis on spectral content preservation. Enhanced MS images of the lunar surface can enable new science and maximize the science return for current and future missions.

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Mahanti, P., M. S. Robinson, H. Sato, A. Awumah, and M. Henriksen. "ENHANCEMENT OF SPATIAL RESOLUTION OF THE LROC WIDE ANGLE CAMERA IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 685–92. http://dx.doi.org/10.5194/isprs-archives-xli-b7-685-2016.

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Image fusion, a popular method for resolution enhancement in Earth-based remote sensing studies involves the integration of geometric (sharpness) detail of a high-resolution panchromatic (Pan) image and the spectral information of a lower resolution multi-spectral (MS) image. Image fusion with planetary images is not as widespread as with terrestrial studies, although successful application of image fusion can lead to the generation of higher resolution MS image data. A comprehensive comparison of six image fusion algorithms in the context of lunar images is presented in this work. Performance of these algorithms is compared by visual inspection of the high-resolution multi-spectral products, derived products such as band-to-band ratio and composite images, and performance metrics with an emphasis on spectral content preservation. Enhanced MS images of the lunar surface can enable new science and maximize the science return for current and future missions.

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Jiang, Hong-Kun, Xiao-Lin Tian, and Ao-Ao Xu. "A new segmentation algorithm for lunar surface terrain based on CCD images." Research in Astronomy and Astrophysics 15, no. 9 (August 28, 2015): 1604–12. http://dx.doi.org/10.1088/1674-4527/15/9/016.

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McConnochie, T. "A Search for Water Ice at the Lunar Poles with Clementine Images." Icarus 156, no. 2 (April 2002): 335–51. http://dx.doi.org/10.1006/icar.2001.6765.

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Denevi, Brett W., Steven D. Koeber, Mark S. Robinson, W. Brent Garry, B. Ray Hawke, Thanh N. Tran, Samuel J. Lawrence, et al. "Physical constraints on impact melt properties from Lunar Reconnaissance Orbiter Camera images." Icarus 219, no. 2 (June 2012): 665–75. http://dx.doi.org/10.1016/j.icarus.2012.03.020.

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Ye, Mengjie, Jian Li, Yanyan Liang, Zhanchuan Cai, and Zesheng Tang. "Automatic seamless stitching method for CCD images of Chang’E-1 lunar mission." Journal of Earth Science 22, no. 5 (September 30, 2011): 610–18. http://dx.doi.org/10.1007/s12583-011-0212-7.

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Liu, W. C., and B. Wu. "PHOTOMETRIC STEREO SHAPE-AND-ALBEDO-FROM-SHADING FOR PIXEL-LEVEL RESOLUTION LUNAR SURFACE RECONSTRUCTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W1 (July 25, 2017): 91–97. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w1-91-2017.

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Shape and Albedo from Shading (SAfS) techniques recover pixel-wise surface details based on the relationship between terrain slopes, illumination and imaging geometry, and the energy response (i.e., image intensity) captured by the sensing system. Multiple images with different illumination geometries (i.e., photometric stereo) can provide better SAfS surface reconstruction due to the increase in observations. Photometric stereo SAfS is suitable for detailed surface reconstruction of the Moon and other extra-terrestrial bodies due to the availability of photometric stereo and the less complex surface reflecting properties (i.e., albedo) of the target bodies as compared to the Earth. Considering only one photometric stereo pair (i.e., two images), pixel-variant albedo is still a major obstacle to satisfactory reconstruction and it needs to be regulated by the SAfS algorithm. The illumination directional difference between the two images also becomes an important factor affecting the reconstruction quality. This paper presents a photometric stereo SAfS algorithm for pixel-level resolution lunar surface reconstruction. The algorithm includes a hierarchical optimization architecture for handling pixel-variant albedo and improving performance. With the use of Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC NAC) photometric stereo images, the reconstructed topography (i.e., the DEM) is compared with the DEM produced independently by photogrammetric methods. This paper also addresses the effect of illumination directional difference in between one photometric stereo pair on the reconstruction quality of the proposed algorithm by both mathematical and experimental analysis. In this case, LROC NAC images under multiple illumination directions are utilized by the proposed algorithm for experimental comparison. The mathematical derivation suggests an illumination azimuthal difference of 90 degrees between two images is recommended to achieve minimal error in SAfS reconstruction while results using real data presents similar pattern. Although the algorithm is designed for lunar surface reconstruction, it is likely to be applicable on other extra-terrestrial bodies such as Mars. The results and findings from this research is of significance for the practical use of photometric stereo and SAfS in the domain of planetary remote sensing and mapping.

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Li, Chunlai, Yan Su, Elena Pettinelli, Shuguo Xing, Chunyu Ding, Jianjun Liu, Xin Ren, et al. "The Moon’s farside shallow subsurface structure unveiled by Chang’E-4 Lunar Penetrating Radar." Science Advances 6, no. 9 (February 2020): eaay6898. http://dx.doi.org/10.1126/sciadv.aay6898.

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On 3 January 2019, China’s Chang’E-4 (CE-4) successfully landed on the eastern floor of Von Kármán crater within the South Pole–Aitken Basin, becoming the first spacecraft in history to land on the Moon’s farside. Here, we report the observations made by the Lunar Penetrating Radar (LPR) onboard the Yutu-2 rover during the first two lunar days. We found a signal penetration at the CE-4 landing site that is much greater than that at the CE-3 site. The CE-4 LPR images provide clear information about the structure of the subsurface, which is primarily made of low-loss, highly porous, granular materials with embedded boulders of different sizes; the images also indicate that the top of the mare basal layer should be deeper than 40 m. These results represent the first high-resolution image of a lunar ejecta sequence ever produced and the first direct measurement of its thickness and internal architecture.

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Bhalerao, R. H., S. S. Gedam, and J. Joglekar. "Scan line optimization for Tri stereo planetary images." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3 (August 11, 2014): 33–37. http://dx.doi.org/10.5194/isprsarchives-xl-3-33-2014.

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In this paper, we propose a new scan line optimization method for matching the triplet of images. In the present paper, the triplets are initially matched using an area based local method. The cost is stored in a structure called as the Disparity Space Image (DSI). Using the global minimum of this cost the initial disparity is generated. Next the local minima are considered as potential matches where global minimum gives erroneous results. These local minima are used for optimization of disparity. As the method is a scanned line optimization, it use popularly resampled images. The experiment is performed using Terrain Mapping Camera images from the Chandrayaan-1 mission. In order to validate the result for accuracy, Lunar Orbiter Laser Altimeter dataset from Lunar Reconnaissance Orbiter mission is used. The method is again verified using standard Middlebury stereo dataset with ground truth. From experiments, it has been observed that using optimization technique for triplets, the total number of correct matches has increased by 5–10 % in comparison to direct methods. The method particularly gives good results at smooth regions, where dynamic programming and blockmatching gives limited accuracy.

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Liu, W. C., and B. Wu. "AN INTEGRATED PHOTOGRAMMETRIC AND PHOTOCLINOMETRIC APPROACH FOR PIXEL-RESOLUTION 3D MODELLING OF LUNAR SURFACE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1117–22. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1117-2018.

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High-resolution 3D modelling of lunar surface is important for lunar scientific research and exploration missions. Photogrammetry is known for 3D mapping and modelling from a pair of stereo images based on dense image matching. However dense matching may fail in poorly textured areas and in situations when the image pair has large illumination differences. As a result, the actual achievable spatial resolution of the 3D model from photogrammetry is limited by the performance of dense image matching. On the other hand, photoclinometry (i.e., shape from shading) is characterised by its ability to recover pixel-wise surface shapes based on image intensity and imaging conditions such as illumination and viewing directions. More robust shape reconstruction through photoclinometry can be achieved by incorporating images acquired under different illumination conditions (i.e., photometric stereo). Introducing photoclinometry into photogrammetric processing can therefore effectively increase the achievable resolution of the mapping result while maintaining its overall accuracy. This research presents an integrated photogrammetric and photoclinometric approach for pixel-resolution 3D modelling of the lunar surface. First, photoclinometry is interacted with stereo image matching to create robust and spatially well distributed dense conjugate points. Then, based on the 3D point cloud derived from photogrammetric processing of the dense conjugate points, photoclinometry is further introduced to derive the 3D positions of the unmatched points and to refine the final point cloud. The approach is able to produce one 3D point for each image pixel within the overlapping area of the stereo pair so that to obtain pixel-resolution 3D models. Experiments using the Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC NAC) images show the superior performances of the approach compared with traditional photogrammetric technique. The results and findings from this research contribute to optimal exploitation of image information for high-resolution 3D modelling of the lunar surface, which is of significance for the advancement of lunar and planetary mapping.

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Yordanov, V., M. Scaioni, M. T. Brunetti, M. T. Melis, A. Zinzi, and P. Giommi. "MAPPING LANDSLIDES IN LUNAR IMPACT CRATERS USING CHEBYSHEV POLYNOMIALS AND DEM’S." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 17–24. http://dx.doi.org/10.5194/isprsarchives-xli-b6-17-2016.

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Geological slope failure processes have been observed on the Moon surface for decades, nevertheless a detailed and exhaustive lunar landslide inventory has not been produced yet. For a preliminary survey, WAC images and DEM maps from LROC at 100 m/pixels have been exploited in combination with the criteria applied by Brunetti et al. (2015) to detect the landslides. These criteria are based on the visual analysis of optical images to recognize mass wasting features. In the literature, Chebyshev polynomials have been applied to interpolate crater cross-sections in order to obtain a parametric characterization useful for classification into different morphological shapes. Here a new implementation of Chebyshev polynomial approximation is proposed, taking into account some statistical testing of the results obtained during Least-squares estimation. The presence of landslides in lunar craters is then investigated by analyzing the absolute values off odd coefficients of estimated Chebyshev polynomials. A case study on the Cassini A crater has demonstrated the key-points of the proposed methodology and outlined the required future development to carry out.

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Yordanov, V., M. Scaioni, M. T. Brunetti, M. T. Melis, A. Zinzi, and P. Giommi. "MAPPING LANDSLIDES IN LUNAR IMPACT CRATERS USING CHEBYSHEV POLYNOMIALS AND DEM’S." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 17–24. http://dx.doi.org/10.5194/isprs-archives-xli-b6-17-2016.

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Geological slope failure processes have been observed on the Moon surface for decades, nevertheless a detailed and exhaustive lunar landslide inventory has not been produced yet. For a preliminary survey, WAC images and DEM maps from LROC at 100 m/pixels have been exploited in combination with the criteria applied by Brunetti et al. (2015) to detect the landslides. These criteria are based on the visual analysis of optical images to recognize mass wasting features. In the literature, Chebyshev polynomials have been applied to interpolate crater cross-sections in order to obtain a parametric characterization useful for classification into different morphological shapes. Here a new implementation of Chebyshev polynomial approximation is proposed, taking into account some statistical testing of the results obtained during Least-squares estimation. The presence of landslides in lunar craters is then investigated by analyzing the absolute values off odd coefficients of estimated Chebyshev polynomials. A case study on the Cassini A crater has demonstrated the key-points of the proposed methodology and outlined the required future development to carry out.

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Ren, Zi Hao, Hong Kun Jiang, Wen Liang Du, Xiao Lin Tian, and Ao Ao Xu. "A New Auto-Extraction Algorithm of Lunar Craters for Chang’E Data Based on the Solar Incidence Angle." Applied Mechanics and Materials 599-601 (August 2014): 1333–39. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.1333.

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A new algorithm for detecting lunar craters based on the solar incidence angle has been proposed, which converts the Chang’E CCD images to binary images first by detecting edges in the Chang’E CCD images, then the new algorithm calculates the average angle of the solar incidence angles of each edge, Comparing the average angle of each edge with the solar incidence angle of the whole image to delete those noise/false edges of craters. Finally, the common circle fitting has been implemented to detect craters from those edge images. The new algorithm proposed has been tested on different Mare areas and all testing results had shown that the new algorithm could get a satisfying effect.

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