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New Trends in High Resolution Imagery Processing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 32451

Special Issue Editors


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Guest Editor
Engineering Faculty, Niccolò Cusano University, Via Don Carlo Gnocchi 3, 00166 Rome, Italy
Interests: HRSI; photogrammetry; historical cartography; GIS; GNSS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last twenty years, the exponential diffusion of high-resolution (HR) and very-high-resolution (VHR) satellite, UAV and terrestrial images and the advances in open and close source software and algorithms have stimulated methodological research in this field.

High-resolution satellite imagery (HRSI) became available in 1999 with the launch of IKONOS, the first civil satellite offering a spatial resolution of 1 m for panchromatic images. Since then other high-resolution satellite platforms have been launched with on board technologically advanced sensors that acquire panchromatic and multispectral images with, respectively, sub-metric and metric resolution. In addition, satellite with stereo and tri-stereo capabilities have been implemented to satisfy the increasing need for higher accuracy and larger area coverage for digital model production. Subsequently, the miniaturization of navigation systems has allowed the great diffusion of drones with photogrammetric capabilities.

These recent advances in sensor technology and algorithm development enable the use of HR remote sensing imagery for development of various product as DTM/DEM and DSM, orthophoto and orthophotomosaics, three-dimensional photogrammetric models. The application fields are increasingly developing from landslide and landfill monitoring to archaeological applications, monitoring an active volcanic area, morphological studies and so on.

Independently of application, each product must be validated in order to define the metric level of precision and accuracy. In fact, high and very-high resolution images are affected by deformation mainly due to camera distortions and acquisition geometry, then they must undergo a geometric rectification process in order to be used for metrical purposes.

This Special Issue aims at collecting new developments, methodologies and applications of high and very high-resolution data for remote sensing. We welcome submissions which provide the community with the most recent advancements on all aspects of satellite remote sensing, including but not limited to:

  • Geometric processing (orientation, orthorectification)
  • Geometric quality assessment
  • DSM/DEM/DTM extraction and validation
  • New open-source solutions for high resolution imagery processing
  • Application with multiresolution and multiplatform data
  • New approaches for precision and accuracy assessment
  • Improvements of existing methods for precision and accuracy assessment
  • Monitoring an active volcanic area
  • Landslide and landfill monitoring
  • Archaeological applications
  • New sensors on mobile device (High resolution camera,GNSS and Lidar)
Dr. Francesca Giannone
Dr. Valerio Baiocchi
Guest Editors

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Keywords

  • Orthorectification
  • Accuracy assessment
  • DSM/DEM/DTM
  • Tri-stereo pairs
  • High resolution imagery
  • UAV
  • SfM
  • Satellite imagery
  • New sensors on mobile device (High resolution camera,GNSS and Lidar)

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Published Papers (11 papers)

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Editorial

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2 pages, 174 KiB  
Editorial
New Trends in High-Resolution Imagery Processing
by Valerio Baiocchi and Francesca Giannone
Remote Sens. 2023, 15(8), 2164; https://doi.org/10.3390/rs15082164 - 19 Apr 2023
Cited by 1 | Viewed by 939
Abstract
Photogrammetry is a technique that was limited to a few specific sensors and application fields until a few years ago [...] Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)

Research

Jump to: Editorial

26 pages, 4471 KiB  
Article
Influence of Block Geometry Configuration on Multi-Image Dense Matching
by Nazarena Bruno, Riccardo Roncella, Fabrizio Diotri, Klaus Thoeni and Anna Giacomini
Remote Sens. 2022, 14(15), 3784; https://doi.org/10.3390/rs14153784 - 6 Aug 2022
Cited by 1 | Viewed by 1439
Abstract
Digital photogrammetry is a widespread surveying technique in different fields of application due to its flexibility, versatility and cost-effectiveness. Despite its increasing automation and simplicity, a proper image block design is crucial to ensure high standards of performance and accuracy. Studies on camera [...] Read more.
Digital photogrammetry is a widespread surveying technique in different fields of application due to its flexibility, versatility and cost-effectiveness. Despite its increasing automation and simplicity, a proper image block design is crucial to ensure high standards of performance and accuracy. Studies on camera network design have been largely dealt with in the scientific literature with reference to image orientation process, while they are still poor on dense matching. This paper investigates the influence of different block geometry configurations on multi-image dense matching. Starting from the same orientation solution, dense matching was performed considering different combinations of number of images and base length distance between the first and the last image within a strip. The raster Digital Elevation Models (DEM) resulting from each sequence of images were compared with a reference DEM to assess accuracy and completeness. The tests were conducted using different cameras and at various test sites to assess different survey conditions and generalize the findings. The presented results provide some operational guidance on block geometry optimization to maximize the accuracy and completeness. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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25 pages, 8764 KiB  
Article
How to Orient and Orthorectify PRISMA Images and Related Issues
by Valerio Baiocchi, Francesca Giannone and Felicia Monti
Remote Sens. 2022, 14(9), 1991; https://doi.org/10.3390/rs14091991 - 21 Apr 2022
Cited by 4 | Viewed by 2412
Abstract
The orientation of satellite images is a necessary operation for the correct geometric use of satellite images whether they are used individually to obtain an orthophoto or as stereocouples to extract three-dimensional information. The orientation allows us to reconstruct the correct position on [...] Read more.
The orientation of satellite images is a necessary operation for the correct geometric use of satellite images whether they are used individually to obtain an orthophoto or as stereocouples to extract three-dimensional information. The orientation allows us to reconstruct the correct position on the ground of the single pixels that form the image, which normally can be performed using certain functions of commercial software customised for each specific satellite. These functions read the metadata parameters provided by the satellite operator and use them to correctly orient the images. Unfortunately, these parameters have not been standardised and various satellites report them according to variable conventions, so new satellites or those that are not widely used cannot be oriented automatically. The PRISMA satellite launched by the Italian Space Agency (ASI) releases free hyperspectral and panchromatic images with metric resolution, but there is not yet a standardised procedure for orienting its images and this limits its usability. This paper reports on the first experimentation of orientation and orthorectification of PRISMA (PRecursore IperSpettrale della Missione Applicativa) images carried out using the three most widely used models, namely the rigorous, the Rational Polynomial Coefficients (RPC) and the Rational Polynomial Functions (RPF) tools. The results obtained by interpreting the parameters and making them suitable for use in standard procedures have made it possible to obtain results with an accuracy equal to the maximum resolution of panchromatic images (5 m), thus making it possible to achieve the highest level of geometric accuracy that can be extracted from the images themselves. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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31 pages, 9846 KiB  
Article
SST Anywhere—A Portable Solution for Wide Field Low Earth Orbit Surveillance
by Radu Gabriel Danescu, Razvan Itu, Mircea Paul Muresan, Ana Rednic and Vlad Turcu
Remote Sens. 2022, 14(8), 1905; https://doi.org/10.3390/rs14081905 - 15 Apr 2022
Cited by 7 | Viewed by 3092
Abstract
The low-Earth orbit (LEO) is filled with active satellites, but also with space debris, which need constant observation. The orbiting objects may be affected by collisions or by atmospheric drag, and therefore they can change their orbit or even fall to the ground, [...] Read more.
The low-Earth orbit (LEO) is filled with active satellites, but also with space debris, which need constant observation. The orbiting objects may be affected by collisions or by atmospheric drag, and therefore they can change their orbit or even fall to the ground, a process known as reentry. The low altitude of these objects (below 2000 km, usually even below 1000 km) means that at given time they can be observed from a limited range of locations on the Earths’ surface, and therefore having multiple, easy to set up observation stations can be extremely useful. This paper presents a portable hardware solution for on-demand wide-field surveillance of the LEO region, the image processing algorithms for detecting the satellite streaks and for joining these streaks into tracklets, and the solution for astrometrical reduction and generating the result file for each tracklet. An automatic validation solution that is able to automatically identify the detected satellites and compute the measurement angular errors is also presented. The acquisition and processing system is built with commercially available items of low and moderate costs and is capable of on-site acquisition and real-time processing of images. The acquired images are processed by background subtraction, analysis of the difference between frames, extraction of elongated objects corresponding to the satellite streaks, and forming trajectories (tracklets) from consecutive detections. The pixel coordinates of the tracklets are converted to angular coordinates using the tools from Astrometry.net, subsequently filtered for improving the accuracy. The results are validated by using daily updated orbital parameters (TLEs), which are used to predict the angular positions that are subsequently matched with the detection results. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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18 pages, 3478 KiB  
Article
No-Reference Quality Assessment of Pan-Sharpening Images with Multi-Level Deep Image Representations
by Igor Stępień and Mariusz Oszust
Remote Sens. 2022, 14(5), 1119; https://doi.org/10.3390/rs14051119 - 24 Feb 2022
Cited by 3 | Viewed by 2048
Abstract
The Pan-Sharpening (PS) techniques provide a better visualization of a multi-band image using the high-resolution single-band image. To support their development and evaluation, in this paper, a novel, accurate, and automatic No-Reference (NR) PS Image Quality Assessment (IQA) method is proposed. In the [...] Read more.
The Pan-Sharpening (PS) techniques provide a better visualization of a multi-band image using the high-resolution single-band image. To support their development and evaluation, in this paper, a novel, accurate, and automatic No-Reference (NR) PS Image Quality Assessment (IQA) method is proposed. In the method, responses of two complementary network architectures in a form of extracted multi-level representations of PS images are employed as quality-aware information. Specifically, high-dimensional data are separately extracted from the layers of the networks and further processed with the Kernel Principal Component Analysis (KPCA) to obtain features used to create a PS quality model. Extensive experimental comparison of the method on the large database of PS images against the state-of-the-art techniques, including popular NR methods adapted in this study to the PS IQA, indicates its superiority in terms of typical criteria. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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16 pages, 3642 KiB  
Article
Digital Terrain Modelling by Remotely Piloted Aircraft: Optimization and Geometric Uncertainties in Precision Coffee Growing Projects
by Lucas Santos Santana, Gabriel Araújo e Silva Ferraz, Diego Bedin Marin, Rafael de Oliveira Faria, Mozarte Santos Santana, Giuseppe Rossi and Enrico Palchetti
Remote Sens. 2022, 14(4), 911; https://doi.org/10.3390/rs14040911 - 14 Feb 2022
Cited by 5 | Viewed by 2273
Abstract
The implantation of coffee crop plantations requires cartographic data for dimensioning areas and planning the planting line. Digital terrain models (DTMs) obtained from remotely piloted aircraft (RPA) can contribute to efficient data collection for topography making this technique applicable to precision coffee projects. [...] Read more.
The implantation of coffee crop plantations requires cartographic data for dimensioning areas and planning the planting line. Digital terrain models (DTMs) obtained from remotely piloted aircraft (RPA) can contribute to efficient data collection for topography making this technique applicable to precision coffee projects. Aiming to achieve efficiency in the collection, processing and photogrammetric products quality, flight configurations and image processing were evaluated. Two hundred sixty-five points obtained by Global Navigation Satellite System (GNSS) receivers characterized the topographic surface. Then eighteen flight missions were carried out by RPA in the configurations of altitude above ground level (AGL) and frontal and lateral image overlay. In addition, different point cloud formats evaluated the image processing (time) efficiency in DTM. Flights performed at 120 m AGL and 80 × 80% overlap showed higher assertiveness and efficiency in generation DTMs. The 90 m AGL flight showed great terrain detail, causing significant surface differences concerning the topography obtained by GNSS. An increase in image overlap requires longer processing times, not contributing linearly to the geometric quality of orthomosaic. Slope ranges up to 20% are considered reliable for precision coffee growing projects; above 20% overestimates the slope values of the land. Changes in flight settings and image processing are satisfactory for precision coffee projects. Image overlap reduction was significant in reducing the processing time without influencing the quality of the DTMs. In addition, image processing performed in shallow point clouds did not interfere with the DTMs quality. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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23 pages, 17671 KiB  
Article
3MRS: An Effective Coarse-to-Fine Matching Method for Multimodal Remote Sensing Imagery
by Zhongli Fan, Yuxian Liu, Yuxuan Liu, Li Zhang, Junjun Zhang, Yushan Sun and Haibin Ai
Remote Sens. 2022, 14(3), 478; https://doi.org/10.3390/rs14030478 - 20 Jan 2022
Cited by 19 | Viewed by 3310
Abstract
The fusion of image data from multiple sensors is crucial for many applications. However, there are significant nonlinear intensity deformations between images from different kinds of sensors, leading to matching failure. To address this need, this paper proposes an effective coarse-to-fine matching method [...] Read more.
The fusion of image data from multiple sensors is crucial for many applications. However, there are significant nonlinear intensity deformations between images from different kinds of sensors, leading to matching failure. To address this need, this paper proposes an effective coarse-to-fine matching method for multimodal remote sensing images (3MRS). In the coarse matching stage, feature points are first detected on a maximum moment map calculated with a phase congruency model. Then, feature description is conducted using an index map constructed by finding the index of the maximum value in all orientations of convolved images obtained using a set of log-Gabor filters. At last, several matches are built through image matching and outlier removal, which can be used to estimate a reliable affine transformation model between the images. In the stage of fine matching, we develop a novel template matching method based on the log-Gabor convolution image sequence and match the template features with a 3D phase correlation matching strategy, given that the initial correspondences are achieved with the estimated transformation. Results show that compared with SIFT, and three state-of-the-art methods designed for multimodal image matching, PSO-SIFT, HAPCG, and RIFT, only 3MRS successfully matched all six types of multimodal remote sensing image pairs: optical–optical, optical–infrared, optical–depth, optical–map, optical–SAR, and day–night, with each including ten different image pairs. On average, the number of correct matches (NCM) of 3MRS was 164.47, 123.91, 4.88, and 4.33 times that of SIFT, PSO-SIFT, HAPCG, and RIFT for the successfully matched image pairs of each method. In terms of accuracy, the root-mean-square error of correct matches for 3MRS, SIFT, PSO-SIFT, HAPCG, and RIFT are 1.47, 1.98, 1.79, 2.83, and 2.45 pixels, respectively, revealing that 3MRS got the highest accuracy. Even though the total running time of 3MRS was the longest, the efficiency for obtaining one correct match is the highest considering the most significant number of matches. The source code of 3MRS and the experimental datasets and detailed results are publicly available. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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17 pages, 13575 KiB  
Article
On the Use of Tri-Stereo Pleiades Images for the Morphometric Measurement of Dolines in the Basaltic Plateau of Azrou (Middle Atlas, Morocco)
by Maria Teresa Melis, Luca Pisani and Jo De Waele
Remote Sens. 2021, 13(20), 4087; https://doi.org/10.3390/rs13204087 - 13 Oct 2021
Cited by 9 | Viewed by 2559
Abstract
Hundreds of large and deep collapse dolines dot the surface of the Quaternary basaltic plateau of Azrou, in the Middle Atlas of Morocco. In the absence of detailed topographic maps, the morphometric study of such a large number of features requires the use [...] Read more.
Hundreds of large and deep collapse dolines dot the surface of the Quaternary basaltic plateau of Azrou, in the Middle Atlas of Morocco. In the absence of detailed topographic maps, the morphometric study of such a large number of features requires the use of remote sensing techniques. We present the processing, extraction, and validation of depth measurements of 89 dolines using tri-stereo Pleiades images acquired in 2018–2019 (the European Space Agency (ESA) © CNES 2018, distributed by Airbus DS). Satellite image-derived DEMs were field-verified using traditional mapping techniques, which showed a very good agreement between field and remote sensing measures. The high resolution of these tri-stereo images allowed to automatically generate accurate morphometric datasets not only regarding the planimetric parameters of the dolines (diameters, contours, orientation of long axes), but also for what concerns their depth and altimetric profiles. Our study demonstrates the potential of using these types of images on rugged morphologies and for the measurement of steep depressions, where traditional remote sensing techniques may be hindered by shadow zones and blind portions. Tri-stereo images might also be suitable for the measurement of deep and steep depressions (skylights and collapses) on Martian and Lunar lava flows, suitable targets for future planetary cave exploration. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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23 pages, 5510 KiB  
Article
Automation of Pan-Sharpening Methods for Pléiades Images Using GIS Basic Functions
by Emanuele Alcaras, Claudio Parente and Andrea Vallario
Remote Sens. 2021, 13(8), 1550; https://doi.org/10.3390/rs13081550 - 16 Apr 2021
Cited by 16 | Viewed by 4645
Abstract
Pan-sharpening methods allow the transfer of higher resolution panchromatic images to multispectral ones concerning the same scene. Different approaches are available in the literature, and only a part of these approaches is included in remote sensing software for automatic application. In addition, the [...] Read more.
Pan-sharpening methods allow the transfer of higher resolution panchromatic images to multispectral ones concerning the same scene. Different approaches are available in the literature, and only a part of these approaches is included in remote sensing software for automatic application. In addition, the quality of the results supplied by a specific method varies according to the characteristics of the scene; for consequence, different algorithms must be compared to find the best performing one. Nevertheless, pan-sharpening methods can be applied using GIS basic functions in the absence of specific pan-sharpening tools, but this operation is expensive and time-consuming. This paper aims to explain the approach implemented in Quantum GIS (QGIS) for automatic pan-sharpening of Pléiades images. The experiments are carried out on data concerning the Greek island named Lesbo. In total, 14 different pan-sharpening methods are applied to reduce pixel dimensions of the four multispectral bands from 2 m to 0.5 m. The automatic procedure involves basic functions already included in GIS software; it also permits the evaluation of the quality of the resulting images supplying the values of appropriate indices. The results demonstrate that the approach provides the user with the highest performing method every time, so the best possible fused products are obtained with minimal effort in a reduced timeframe. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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21 pages, 9909 KiB  
Article
Object-Based Predictive Modeling (OBPM) for Archaeology: Finding Control Places in Mountainous Environments
by Luigi Magnini and Cinzia Bettineschi
Remote Sens. 2021, 13(6), 1197; https://doi.org/10.3390/rs13061197 - 21 Mar 2021
Cited by 8 | Viewed by 3011
Abstract
This contribution examines the potential of object-based image analysis (OBIA) for archaeological predictive modeling starting from elevation data, by testing a ruleset for the location of “control places” on two test areas in the Alpine environment (northern Italy). The ruleset was developed on [...] Read more.
This contribution examines the potential of object-based image analysis (OBIA) for archaeological predictive modeling starting from elevation data, by testing a ruleset for the location of “control places” on two test areas in the Alpine environment (northern Italy). The ruleset was developed on the western Asiago Plateau (Vicenza Province, Veneto) and subsequently re-applied (semi)automatically in the Isarco Valley (South Tirol). Firstly, we considered the physiographic, climatic, and morphological characteristics of the selected areas and we applied 3 DTM processing techniques: Slope, local dominance, and solar radiation. Subsequently, we employed an object-based approach to classification. Solar radiation, local dominance, and slope were visualized as a three-layer RGB image that was segmented with the multiresolution algorithm. The classification was implemented with a ruleset that selected only image–objects with high local dominance and solar radiation, but low slope, which were considered more suitable parameters for human occupation. The classification returned five areas on the Asiago Plateau that were remotely and ground controlled, confirming anthropic exploitation covering a time span from protohistory (2nd-1st millennium BC) to the First World War. Subsequently, the same model was applied to the Isarco Valley to verify the replicability of the method. The procedure resulted in 36 potential control places which find good correspondence with the archaeological sites discovered in the area. Previously unknown contexts were further controlled using very high-resolution (VHR) aerial images and digital terrain model (DTM) data, which often suggested a possible (pre-proto)historic human frequentation. The outcomes of the analysis proved the feasibility of the approach, which can be exported and applied to similar mountainous landscapes for site predictivity analysis. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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17 pages, 8400 KiB  
Article
Integrated Geomatic Techniques for Georeferencing and Reconstructing the Position of Underground Archaeological Sites: The Case Study of the Augustus Sundial (Rome)
by Valerio Baiocchi, Raffaella Brigante, Silvio Del Pizzo, Francesca Giannone, Matteo Onori, Fabio Radicioni, Aurelio Stoppini, Grazia Tosi, Salvatore Troisi and Marta Baumgartner
Remote Sens. 2020, 12(24), 4064; https://doi.org/10.3390/rs12244064 - 11 Dec 2020
Cited by 6 | Viewed by 2269
Abstract
A large part of the archaeological remains still to be discovered and excavated are not in remote and depopulated areas of the earth but are often beneath urban centres that have buried them with centuries of debris and later constructions. Excavating in these [...] Read more.
A large part of the archaeological remains still to be discovered and excavated are not in remote and depopulated areas of the earth but are often beneath urban centres that have buried them with centuries of debris and later constructions. Excavating in these contexts is much more complex than digging in rural or sparsely inhabited areas because of the constraints imposed by existing buildings and infrastructure. It should also be considered that within an urbanised area, any archaeological remains are concentrated in the subsoil of the historic centre, which is, therefore, often surmounted by buildings that are more recent than the remains but historical as well, and thus, of considerable value and vulnerability. For this reason, an archaeological excavation in an urban area must be preceded by a real feasibility study, where the potential risks for the structures above are minimised and accurately quantified. In many situations, as in the case under study, the discovery of a small segment of a structure is the only clue to reconstruct the development of the remaining part still to be excavated, which may stretch tens or hundreds of metres away from the measurable part. As a consequence, an error of a few centimetres in the survey of the excavated part can lead to errors of metres in estimating the positions of the far parts still to be excavated, and this, in many cases, as in the one under study, must absolutely be avoided. In practice, high-precision geomatic surveys, in support of the archaeological and historical interpretation of the observable structures, will help to establish the exact locations to possibly continue the excavations, helping the accurate planning of the excavation itself. Here, we have shown how the various techniques, compared to each other, have made it possible to reconstruct the location of a short stretch (less than 7 m) of the Emperor Augustus’ Sundial, the only currently visible evidence of a scientific instrument of imposing dimensions (tens of metres in length and height) that served to define some of the characteristics of the calendar that we still use today. The portion of the sundial currently observable, according to the most reliable hypotheses, is located approximately at one end of a structure and extends for several tens of metres. The accurate positioning of the observable parts in a geodetic reference system will enable to identify with certainty the possible areas in which excavation may continue and will also allow to accurately reconstruct the principle of operation of the sundial through an approach that could be defined as “reverse engineering” of the scientific instrument itself. The aim of this work is to study and thus define the combination and integration of existing geomatic techniques for this specific field of application. Full article
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
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