Academic literature on the topic 'Aeromagnetic data image processing'

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Journal articles on the topic "Aeromagnetic data image processing"

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Kowalik, W. S., and W. E. Glenn. "Image processing of aeromagnetic data and integration with Landsat images for improved structural interpretation." GEOPHYSICS 52, no. 7 (July 1987): 875–84. http://dx.doi.org/10.1190/1.1442358.

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Digital image processing of aeromagnetic data from three mineral prospects significantly improved the existing structural interpretations that were made from contour maps of the aeromagnetic data. Useful image‐processing techniques include (1) presentation as small‐scale, gray‐level images, (2) local contrast enhancement, (3) artificial illumination, and (4) directional filtering. Digital processing also enables direct comparison between Landsat data and aeromagnetic data. Interpretations were improved by the study of the integrated data sets. Images of aeromagnetic data from one prospect in a Precambrian granite‐greenstone terrane show major folds and faults that were not previously recognized from contour maps of the aeromagnetic data. A Landsat Multispectral Scanner (MSS) image shows the subtle surface expression of two folds. The newly identified structures point to additional prospective ground in the search for volcanogenic massive sulfide deposits in the area. Aeromagnetic data from a second prospect are complicated by a young, north‐south striking, strongly magnetic, diabase dike swarm. Directional filtering and artificial illumination of the aeromagnetic data effectively remove the response of the dikes and enhance the earlier structural and lithologic features. The combined interpretation of illuminated aeromagnetic and registered Landsat Thematic Mapper (TM) images for a third prospect added several significant faults that were previously unrecognized from separate interpretations of contour maps of aeromagnetic data and the Landsat image.
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Yigui, Lionel Cedric, Theophile Ndougsa-Mbarga, Arsène Meying, and Olivier Ulrich-Igor Owono-Amougou. "Detection of sub-surface fractures based on filtering, modeling, and interpreting aeromagnetic data in the Deng Deng – Garga Sarali area, Eastern Cameroon." Open Geosciences 14, no. 1 (January 1, 2022): 646–62. http://dx.doi.org/10.1515/geo-2022-0357.

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Abstract The aeromagnetic anomalies existing in the Deng Deng – Garga Sarali region in Eastern Cameroon were filtered for a structural study of the region’s subsoil. This study presents the results of lineaments and fractures extracted by aeromagnetic image processing methods and compared with scientific data to obtain potential terrain models in the study area. The methodological approach used is based on the filtering of aeromagnetic image by using the analytical signal, the Euler deconvolution, and 2D3/4 modeling, to establish the maps of the lineaments and faults of the study area and their characteristics, and also to propose three models from three previously chosen profiles. Analytical signal and Euler deconvolution techniques have been applied to aeromagnetic anomalies to highlight the relationship between the depth and the source of magnetic anomalies, two parameters whose importance in geoexploration and modeling of the body is essential. We identified the potential contacts by interpretation of the deep Euler anomalies, these are highlighted on the basis of a certain similarity between the maps of the total magnetic field, the map of the analytical signal, the map of the maxima of the gradient horizontal, and geological map. Euler’s map of solutions correlates well with the edges of certain superficial and deep causative bodies.
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Soulaimani, Ayoub, Saïd Chakiri, Saâd Soulaimani, Ahmed Manar, Zohra Bejjaji, Abdelhalim Miftah, Mohammed Amine Zerdeb, Yaacoub Zidane, Mustapha Boualoul, and Anselme Muzirafuti. "Semi-Automatic Image Processing System of Aeromagnetic Data for Structural and Mining Investigations (Case of Bou Azzer Inlier, Central Anti-Atlas, Morocco)." Applied Sciences 12, no. 21 (November 7, 2022): 11270. http://dx.doi.org/10.3390/app122111270.

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Numerical analysis of geophysical data to uncover Precambrian belts and probably to enclose mineral deposits is becoming once more communal in mining activity. The method is founded on typifying zones branded to comprehend deposits and looking for analogous areas. The proposed work outlines a semi-automatic image processing system for the structural and mining investigation of the Bou Azzer inlier, which varies from preceding approaches as it is centered only on aeromagnetic data. The aeromagnetic signature of what seem to be geologically expressive features are pursued within the aeromagnetic items. Cobalt and associated mineralizations in the Bou Azzer inlier are recognized to arise nearby main crustal discontinuities revealing as significant shear zones, which turn act as drains for mineralizing fluids. Mineralization occurs in sectors of structural complexity beside the shear zones. Developing towards the semi-automatic uncovering of such regions, the furthermost prospective extents are those everywhere inferred structural complexity occurs next to the regions of magnetic discontinuity. The proposed method is mainly based on the approach developed by the center for exploration targeting. The study was led by means of aeromagnetic data from the Bou Azzer inlier, which is considered one of the most productive and prospective regions for minerals and base metal mineralization in Morocco. The combined results obtained from geological and geophysical data prove that prospective areas have a dominant trend of NNE-SSW, NW-SE, NNW-SSE, E-W, and NE-SW directions. The CET Grid and Porphyry Analyses show that the probable porphyry mineral deposit locations mainly concentrated in the center of inlier, the Foum Zguid dyke, and northern and eastern part, which correspond to the Bou Azzer ophiolitic complex and platform deposits of the Lower Neoproterozoic Tachdamt-Bleïda.
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Naprstek, Tomas, and Richard S. Smith. "A new method for interpolating linear features in aeromagnetic data." GEOPHYSICS 84, no. 3 (May 1, 2019): JM15—JM24. http://dx.doi.org/10.1190/geo2018-0156.1.

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When aeromagnetic data are interpolated to make a gridded image, thin linear features can result in “boudinage” or “string of beads” artifacts if the anomalies are at acute angles to the traverse lines. These artifacts are due to the undersampling of these types of features across the flight lines, making it difficult for most interpolation methods to effectively maintain the linear nature of the features without user guidance. The magnetic responses of dikes and dike swarms are typical examples of the type of geologic feature that can cause these artifacts; thus, these features are often difficult to interpret. Many interpretation methods use various enhancements of the gridded data, such as horizontal or vertical derivatives, and these artifacts are often exacerbated by the processing. Therefore, interpolation methods that are free of these artifacts are necessary for advanced interpretation and analysis of thin, linear features. We have developed a new interpolation method that iteratively enhances linear trends across flight lines, ensuring that linear features are evident on the interpolated grid. Using a Taylor derivative expansion and structure tensors allows the method to continually analyze and interpolate data along anisotropic trends, while honoring the original flight line data. We applied this method to synthetic data and field data, which both show improvement over standard bidirectional gridding, minimum curvature, and kriging methods for interpolating thin, linear features at acute angles to the flight lines. These improved results are also apparent in the vertical derivative enhancement of field data. The source code for this method has been made publicly available.
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McDonald, A. J. W., C. J. N. Fletchert, R. M. Carruthers, D. Wilson, and R. B. Evans. "Interpretation of the regional gravity and magnetic surveys of Wales, using shaded relief and Euler deconvolution techniques." Geological Magazine 129, no. 5 (September 1992): 523–31. http://dx.doi.org/10.1017/s0016756800021683.

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AbstractRegional gravity and aeromagnetic data of Wales have been processed using a variety of techniques. Image processing has greatly assisted qualitative interpretation, whilst automated procedures have provided additional quantitative information. The shaded relief images emphasize gradients in the potential fields, and are useful for displaying strong linear features. The Euler deconvolution method produces plotted solution maps, which define the position of the source of the gravity and magnetic anomalies. Euler solution maps of Wales and the adjacent continental shelf are presented for the first time. These maps are interpreted in relation to the known geology, with special emphasis on the Lower Palaeozoic Welsh Basin. It is proposed that the Euler solutions define a network of fault-bounded blocks within the Precambrian basement.
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Thurston, Jeffrey B., and Richard S. Smith. "Automatic conversion of magnetic data to depth, dip, and susceptibility contrast using the SPI (TM) method." GEOPHYSICS 62, no. 3 (May 1997): 807–13. http://dx.doi.org/10.1190/1.1444190.

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The Source Parameter Imaging (SPI™) method computes source parameters from gridded magnetic data. The method assumes either a 2-D sloping contact or a 2-D dipping thin‐sheet model and is based on the complex analytic signal. Solution grids show the edge locations, depths, dips, and susceptibility contrasts. The estimate of the depth is independent of the magnetic inclination, declination, dip, strike and any remanent magnetization; however, the dip and the susceptibility estimates do assume that there is no remanent magnetization. Image processing of the source‐parameter grids enhances detail and provides maps that facilitate interpretation by nonspecialists. The SPI method tests successfully on synthetic profile and gridded data. SPI maps derived from aeromagnetic data acquired over the Peace River Arch area of northwestern Canada correlate well with known basement structure and furthermore show that the Ksituan Magmatic Arc can be divided into several susceptibility subdomains.
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Chacksfield, B. C., W. De Vos, L. D'Hooge, M. Dusar, M. K. Lee, C. Poitevin, C. P. Royles, and J. Verniers. "A new look at Belgian aeromagnetic and gravity data through image-based display and integrated modelling techniques." Geological Magazine 130, no. 5 (September 1993): 583–91. http://dx.doi.org/10.1017/s0016756800020884.

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AbstractDigital processing and image-based display techniques have been used to generate contour and shaded-relief maps of Belgian aeromagnetic data at a scale of 1:300000 for the whole of Belgium. These highlight the important anomalies and structural trends, particularly over the Brabant Massif. North and vertically illuminated shaded-relief plots, enhanced structural belts trending west–east to northwest–southeast in the Brabant Massif and west–east to southwest–northeast in the core of the Ardennes. The principal magnetic lineaments have been identified from the shaded-relief plots and tentatively correlated to basement structures. Most short lineaments are correlated with individual folds while the more extensive lineaments are correlated with large scale fault structures. Magnetic highs within the Brabant Massif are attributed to folded sediments of the Tubize Group. The magnetic basement in the east of Belgium is sinistrally displaced to the north by an inferred deep NNW–SSE crustal fracture. The Bouguer anomaly map of Belgium identifies the Ardennes as a negative area, and the Brabant Massif as a positive area, with the exception of a WNW–trending gravity low in its western part. The southern margin of the Brabant Massif is defined by a steep gravity gradient coincident with the Faille Bordiere (Border Fault). Trial modelling of the gravity and magnetic data, carried out along profiles across the Brabant and Stavelot massifs, has identified probable acid igneous intrusions in the western part of the Brabant Massif, and a deep magnetic lower density body underlying the whole Ardennes region, which is thought to be a distinctive Precambrian crustal block.
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Pettifer, G., A. Tabassi, and B. Simons. "A NEW LOOK AT THE STRUCTURAL TRENDS IN THE ONSHORE OTWAY BASIN, VICTORIA, USING IMAGE PROCESSING OF GEOPHYSICAL DATA." APPEA Journal 31, no. 1 (1991): 213. http://dx.doi.org/10.1071/aj90016.

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Although the Otway Basin is oriented west-north-westerly, and previously recognised major structural elements follow a similar trend, other structural trends have been found on recently obtained geophysical data.In 1989, an aeromagnetic and radiometric survey of the onshore Otway Basin was completed for the Victorian Department of Industry and the Bureau of Mineral Resources, Geology and Geophysics. This survey, together with a recent gravity compilation by the Geological Survey of Victoria, enables analysis of magnetic and gravity data trends reflecting basement and intra-basin structure.The trend analysis was carried out using modern image processing techniques including simulation of real-time sun-angles of the magnetic and gravity data, and composite images of the radiometric data, to highlight lineaments. This technology enables integration of magnetic, gravity, radiometric and, potentially, seismic, Landsat, topography and bathymetry data for basin structure analysis.The magnetic, gravity and radiometric trend analysis was compared to an earlier Landsat study (Baker, 1980) and a previous seismic data compilation of the Otway Basin (Megallaa, 1986).The present study has revealed the significance of major early Palaeozoic north-south and east-north-east to easterly trends. The latter trends have not previously been identified or discussed in earlier basin reviews. There appears to be a difference between trends reflected in the radiometric and seismic data and trends apparent in the gravity and magnetic data. This could indicate a change in principal stress directions during the evolution of the basin. The shape of the northern margin of the basin appears to be controlled by major north-easterly structures.
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Rosa, João Willy Corrêa, José Wilson Corrêa Rosa, and Götz Bokelmann. "Lateral variation of crustal properties from aerogeophysical data in northern Brazil." GEOPHYSICS 82, no. 5 (September 1, 2017): J39—J60. http://dx.doi.org/10.1190/geo2016-0206.1.

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A new method is proposed for the study of crustal azimuthal anisotropy, and the lateral variation of other crustal aerogeophysical parameters, using a quantitative approach. The processing of a large, newly acquired, high-resolution set of aerogeophysical data is considered using the existing Radon transform and the geostatistical analysis approaches. The data set includes an area of the Guyana shield, in northern Brazil, which was not included in previous surveys. The area is covered by dense rain forest vegetation and thick soil layers. Parameterization was performed considering the possible anisotropic character of the geophysical 2D data. Application of the newly proposed geostatistical data processing yielded high-resolution images of the lateral variation of quantitative geophysical parameters, which indicate good correlation with previously determined seismic anisotropy in the area. Average anisotropy as measured by the Radon transform and variogram analysis is scale dependent. At scales greater than [Formula: see text], the results seem to match those of the previous seismic studies. Images of the derived quantitative parameters from magnetic and radiometric data in the shield area indicate sharp changes that follow the known geologic changes observable in the survey area. Observed large-scale anisotropy in the area seems to be autocorrelated with two different geochronological provinces of the Amazonian craton. Application of the new technique to two other lower resolution aeromagnetic surveys located on the Amazon basin has produced two different results, including one successful data treatment of the aeromagnetic survey. The results obtained for this area indicate that the sedimentary cover seems to play almost no role in the observed magnetic anomaly anisotropy in the middle Amazon basin area. Most of the observed magnetic anomalies appear to be controlled by the continuing geologic features of the cratonic basement.
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Rahman, Aqeel, Inass Almallah, and Ahmed Mousa. "Lineaments Tracing of Magnetic Sources Depending on the Aeromagnetic Data: Case Study in Salman Basin and Surrounding Areas, Southern Desert of Iraq." Iraqi Geological Journal 55, no. 1D (April 30, 2022): 184–98. http://dx.doi.org/10.46717/igj.55.1d.14ms-2022-04-30.

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This study deals with the processing and analysis of aeromagnetic data for an area covering the region of Salman Basin within AL- Muthanna, Iraq. The objective of this study is to use the available satellite images and aeromagnetic data to investigate the boundaries of geological structures. For further understanding of the tectonic of the study area, the Centre for Exploration Targeting Grid Analysis extension which is available in Oasis montaj software was applied to the data. It is proposed that it provides unbiased results, but to check the results Tilt Derivative or local phase derivative is used where the zero-contour line of the tilt derivative strongly delineates the edges of structures. Also, the drainage pattern for the basin is done using Geographic Information System and Digital Elevation Model raster to see if the drainage is affected by the subsurface lineaments that are determined using the Centre for Exploration Targeting technique. As a result, the deep main linear features follow the general trend of the main faults that formed the Salman Basin. The new lineaments were discovered using the Exploration Targeting grid analysis, zero contour of. There are two systems of lineaments in the present study area. The first set is taken the NW-NE direction perpendicular to the extensional structures, while the second set has the NS-EW direction.
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Dissertations / Theses on the topic "Aeromagnetic data image processing"

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Magaia, Luis. "Processing Techniques of Aeromagnetic Data. Case Studies from the Precambrian of Mozambique." Thesis, Uppsala universitet, Geofysik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-183714.

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During 2002-2006 geological field work were carried out in Mozambique. The purpose was to check the preliminary geological interpretations and also to resolve the problems that arose during the compilation of preliminary geological maps and collect samples for laboratory studies. In parallel, airborne geophysical data were collected in many parts of the country to support the geological interpretation and compilation of geophysical maps. In the present work the aeromagnetic data collected in 2004 and 2005 in two small areas northwest of Niassa province and another one in eastern part of Tete province is analysed using GeosoftTM. The processing of aeromagnetic data began with the removal of diurnal variations and corrections for IGRF model of the Earth in the data set. The study of the effect of height variations on recorded magnetic field, levelling and interpolation techniques were also studied. La Porte interpolation showed to be a good tool for interpolation of aeromagnetic data using measured horizontal gradient. Depth estimation techniques are also used to obtain semi-quantitative interpretation of geological bodies. It was showed that many features in the study areas are located at shallow depth (less than 500 m) and few geological features are located at depths greater than 1000 m. This interpretation could be used to draw conclusions about the geology or be incorporated into further investigations in these areas.
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Chintala, Venkatram Reddy. "Digital image data representation." Ohio : Ohio University, 1986. http://www.ohiolink.edu/etd/view.cgi?ohiou1183128563.

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Barker, Kelly. "Improved application of remote referencing data in aeromagnetic processing : insights and applications from global geomagnetic modelling." Thesis, University of Liverpool, 2016. http://livrepository.liverpool.ac.uk/3002173/.

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Magnetic surveys are an important method of understanding subsurface geology, however there are several reasons why correction by remote referencing may fail, including local induced effects, activity levels of the field, and simple distance between survey and base station. We look for ways to improve correction by remote referencing using insights from global field models and comparisons of data from a wide range of observatories. We investigate the conditions in which the behaviour of nearby observatories differ from each other, and where the CM4 comprehensive model fails to match the observed behaviour of the local geomagnetic field. The misfits are separated by cause: those due to the activity level of the geomagnetic field, and the location of the observatory. We see that CM4 is a good match to observatories in the conditions it was designed for (mid-latitudes and Kp up to 2), but also that it can produce a good fit to stations out of this range (up to Kp of 3 or 4). The correlation of misfits to CM4 allows us to separate effects due to latitude, and location on the coast. Further investigation allows us to suggest some corrections that may improve the quality and extent of magnetic data gained by surveys in these locations. High latitude stations show changes in behaviour which fall into latitudinally split groups, most likely due to the presence of induced fields from ionospheric currents. Ensuring base station and survey fall into the same grouping would eliminate many of the problems this causes. Geomagnetic storms often lead to survey data being unusable due to their effects. We find that while X component data contains mostly storm signal, the Y and Z components at many stations contain retrievable data. The recovery period of the storm can, for most stations, be used after a regression is applied. We also consider the effects of induced fields due to the tides and the coast effect -well-known effects that can be seen at many stations. We find a correction for the dominant M2 tidal effect using cosine waves. We also find an approximate correction for the coast effect, using cosine or sine waves of the Sq period as appropriate for the station pair chosen. It is also noted that small differences in location can have a large effect on the induced fields, as seen at GUI and TAM, where storms seem to have a smaller than expected effect.
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Dahlberg, Tobias. "Distributed Storage and Processing of Image Data." Thesis, Linköpings universitet, Databas och informationsteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85109.

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Systems operating in a medical environment need to maintain high standards regarding availability and performance. Large amounts of images are stored and studied to determine what is wrong with a patient. This puts hard requirements on the storage of the images. In this thesis, ways of incorporating distributed storage into a medical system are explored. Products, inspired by the success of Google, Amazon and others, are experimented with and compared to the current storage solutions. Several “non-relational databases” (NoSQL) are investigated for storing medically relevant metadata of images, while a set of distributed file systems are considered for storing the actual images. Distributed processing of the stored data is investigated by using Hadoop MapReduce to generate a useful model of the images' metadata.
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JULARDZIJA, MIRHET. "Processing RAW image data in mobile units." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-27724.

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Grosse, Neil G. "Image processing of Red Sea geophysical data." Thesis, University of Newcastle Upon Tyne, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.308392.

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Parker, Greg. "Robust processing of diffusion weighted image data." Thesis, Cardiff University, 2014. http://orca.cf.ac.uk/61622/.

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The work presented in this thesis comprises a proposed robust diffusion weighted magnetic resonance imaging (DW-MRI) pipeline, each chapter detailing a step designed to ultimately transform raw DW-MRI data into segmented bundles of coherent fibre ready for more complex analysis or manipulation. In addition to this pipeline we will also demonstrate, where appropriate, ways in which each step could be optimized for the maxillofacial region, setting the groundwork for a wider maxillofacial modelling project intended to aid surgical planning. Our contribution begins with RESDORE, an algorithm designed to automatically identify corrupt DW-MRI signal elements. While slower than the closest alternative, RESDORE is also far more robust to localised changes in SNR and pervasive image corruptions. The second step in the pipeline concerns the retrieval of accurate fibre orientation distribution functions (fODFs) from the DW-MRI signal. Chapter 4 comprises a simulation study exploring the application of spherical deconvolution methods to `generic' fibre; finding that the commonly used constrained spherical harmonic deconvolution (CSHD) is extremely sensitive to calibration but, if handled correctly, might be able to resolve muscle fODFs in vivo. Building upon this information, Chapter 5 conducts further simulations and in vivo image experimentation demonstrating that this is indeed the case, allowing us to demonstrate, for the first time, anatomically plausible reconstructions of several maxillofacial muscles. To complete the proposed pipeline, Chapter 6 then introduces a method for segmenting whole volume streamline tractographies into anatomically valid bundles. In addition to providing an accurate segmentation, this shape-based method does not require computationally expensive inter-streamline comparisons employed by other approaches, allowing the algorithm to scale linearly with respect to the number of streamlines within the dataset. This is not often true for comparison based methods which in the best case scale in higher linear time but more often by O(N2) complexity.
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Benjamin, Jim Isaac. "Quadtree algorithms for image processing /." Online version of thesis, 1991. http://hdl.handle.net/1850/11078.

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Bhatt, Mittal Gopalbhai. "Detecting glaucoma in biomedical data using image processing /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/939.

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Turkmen, Muserref. "Digital Image Processing Of Remotely Sensed Oceanographic Data." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609948/index.pdf.

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Developing remote sensing instrumentation allows obtaining information about an area rapidly and with low costs. This fact offers a challenge to remote sensing algorithms aimed at extracting information about an area from the available re¬
mote sensing data. A very typical and important problem being interpretation of satellite images. A very efficient approach to remote sensing is employing discrim¬
inant functions to distinguish different landscape classes from satellite images. Various methods on this direction are already studied. However, the efficiency of the studied methods are still not very high. In this thesis, we will improve efficiency of remote sensing algorithms. Besides we will investigate improving boundary detection methods on satellite images.
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Books on the topic "Aeromagnetic data image processing"

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P, Canton Maria, ed. Space image processing. Boca Raton: CRC Press, 1999.

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Al-Shuhail, Abdullatif A., Saleh A. Al-Dossary, and Wail A. Mousa. Seismic Data Interpretation using Digital Image Processing. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119125594.

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Computer image processing in traffic engineering. Taunton, Somerset, England: Research Studies Press, 1991.

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1954-, Woods Richard E., ed. Digital image processing. Reading, Mass: Addison-Wesley Pub. Co, 1993.

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Gonzalez, Rafael C. Digital image processing. 2nd ed. Reading, Mass: Addison-Wesley, 1987.

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Gonzalez, Rafael C. Digital image processing. 3rd ed. Upper Saddle River, N.J: Prentice Hall, 2008.

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1954-, Woods Richard E., ed. Digital image processing. 2nd ed. Upper Saddle River, N.J: Prentice Hall, 2002.

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Paskevich, Valerie F. Conversion of raster image data to vector cartographic data. Reston, VA: U.S. Geological Survey, 1991.

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1954-, Woods Richard E., ed. Digital image processing. 2nd ed. Upper Saddle River, NJ: Prentice Hall, 2002.

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1954-, Woods Richard E., ed. Digital image processing. 3rd ed. Upper Saddle River, N.J: Prentice Hall, 2008.

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Book chapters on the topic "Aeromagnetic data image processing"

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Bidaut, L. "Data/Image Processing." In Spiral CT of the Abdomen, 13–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-56976-0_2.

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Suganya, R., S. Rajaram, and A. Sheik Abdullah. "Image Processing." In Big Data in Medical Image Processing, 46–70. Boca Raton, FL : CRC Press, [2018] | “A science publishers book.”: CRC Press, 2018. http://dx.doi.org/10.1201/b22456-2.

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Bajcsy, Peter, Joe Chalfoun, and Mylene Simon. "Image Processing Algorithms." In Web Microanalysis of Big Image Data, 105–59. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-63360-2_5.

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Sonka, Milan, Vaclav Hlavac, and Roger Boyle. "Image data compression." In Image Processing, Analysis and Machine Vision, 458–76. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-3216-7_12.

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Groth, Edward J. "Astronomical Input to Image Processing Astronomical Output from Image Processing." In Data Analysis in Astronomy, 323–41. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4615-9433-8_29.

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Raffel, Markus, Christian E. Willert, Fulvio Scarano, Christian J. Kähler, Steven T. Wereley, and Jürgen Kompenhans. "Post-processing of PIV Data." In Particle Image Velocimetry, 243–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-68852-7_7.

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Raffel, Markus, Christan E. Willert, and Jürgen Kompenhans. "Post-processing of PIV data." In Particle Image Velocimetry, 147–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03637-2_6.

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Suganya, R., S. Rajaram, and A. Sheik Abdullah. "Image Registration." In Big Data in Medical Image Processing, 71–94. Boca Raton, FL : CRC Press, [2018] | “A science publishers book.”: CRC Press, 2018. http://dx.doi.org/10.1201/b22456-3.

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Allen, R. J., R. D. Ekers, and J. P. Terlouw. "The Groningen Image Processing System." In Data Analysis in Astronomy, 271–302. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4615-9433-8_27.

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Cantoni, Virginio. "New Architectures for Image Processing." In Data Analysis in Astronomy, 479–95. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4615-9433-8_42.

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Conference papers on the topic "Aeromagnetic data image processing"

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Ridsdill-Smith, T. A., M. C. Dentith, and R. D. List. "Applications of wavelet transforms in aeromagnetic data processing." In 6th SAGA Biennial Conference and Exhibition. European Association of Geoscientists & Engineers, 1999. http://dx.doi.org/10.3997/2214-4609-pdb.221.007.

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boufkri, hafsa, Driss El Azzab, Abdelhalim Miftah, and Mohammed Charroud. "Processing and Analysis of aeromagnetic data of North-Eastern Morocco." In The 2nd International Electronic Conference on Mineral Science. Basel, Switzerland: MDPI, 2021. http://dx.doi.org/10.3390/iecms2021-09367.

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Holden, Eun-Jung, Peter Kovesi, Mike C. Dentith, Daniel Wedge, Jason C. Wong, and Shih Ching Fu. "Detection of regions of structural complexity within aeromagnetic data using image analysis." In 2010 25th International Conference of Image and Vision Computing New Zealand (IVCNZ). IEEE, 2010. http://dx.doi.org/10.1109/ivcnz.2010.6148856.

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Gu, Bin, Qingli Li, and Hongying Liu. "Aeromagnetic compensation based on truncated singular value decomposition with an improved parameter-choice algorithm." In 2013 6th International Congress on Image and Signal Processing (CISP). IEEE, 2013. http://dx.doi.org/10.1109/cisp.2013.6743921.

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Caratori Tontini, F. "New Techniques of Geophysical Surveys Data Processing – The Aeromagnetic Anomaly Map of Italy." In 1st EAGE North African/Mediterranean Petroleum & Geosciences Conference & Exhibition. European Association of Geoscientists & Engineers, 2003. http://dx.doi.org/10.3997/2214-4609-pdb.8.t007.

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Vallée, Marc A., James Craven, Larry Newitt, Pierre Keating, Régis Dumont, and Ian Ferguson. "Guidelines for location and use of base station data in aeromagnetic survey processing." In SEG Technical Program Expanded Abstracts 2006. Society of Exploration Geophysicists, 2006. http://dx.doi.org/10.1190/1.2370409.

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Sato, Hédison K., Gustavo R. Gomes, and Edson E. S. Sampaio. "Processing and interpretation of the aeromagnetic data from Curaçá River Valley at Bahia, Brazil." In SEG Technical Program Expanded Abstracts 1998. Society of Exploration Geophysicists, 1998. http://dx.doi.org/10.1190/1.1820576.

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Dushatskiy, Arkadiy, Gerry Lowe, Peter A. N. Bosman, and Tanja Alderliesten. "Data variation-aware medical image segmentation." In Image Processing, edited by Ivana Išgum and Olivier Colliot. SPIE, 2022. http://dx.doi.org/10.1117/12.2608611.

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de Oliveira, Daniel Shkromada, and Marta Silvia Maria Mantovani. "Study of Pratinha-II magnetic anomaly: Acquisition, processing and interpretation of aeromagnetic and gravimetric data." In 12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15-18 August 2011. Society of Exploration Geophysicists and Brazilian Geophysical Society, 2011. http://dx.doi.org/10.1190/sbgf2011-116.

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Li, Jieyu, Jayaram K. Udupa, Yubing Tong, Lisheng Wang, and Drew A. Torigian. "Anatomy segmentation evaluation with sparse ground truth data." In Image Processing, edited by Bennett A. Landman and Ivana Išgum. SPIE, 2020. http://dx.doi.org/10.1117/12.2549327.

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Reports on the topic "Aeromagnetic data image processing"

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Healey, Glenn. Advanced Methods for Representing and Processing Hyperspectral Image Data. Fort Belvoir, VA: Defense Technical Information Center, March 2012. http://dx.doi.org/10.21236/ada581465.

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Rheault, M. M., R. Simard, P. Keating, and M. M. Pelletier. Mineral exploration: digital image processing of LANDSAT, SPOT, magnetic and geochemical data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128045.

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Ellis, Michael G. An Image Processing Technique for Achieving Lossy Compression of Data at Ratios in Excess of 100:1. Fort Belvoir, VA: Defense Technical Information Center, November 1992. http://dx.doi.org/10.21236/ada259218.

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Nelson, B., D. Hardwick, D. A. Forsyth, D. Marcotte, D. Teskey, M. Macpherson, M. Bower, and R. Macnab. Preliminary Report of Data Acquisition and Processing For the 1989 - 1990 Lincoln Sea Aeromagnetic Survey. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1991. http://dx.doi.org/10.4095/131485.

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Bhatt, Parth, Curtis Edson, and Ann MacLean. Image Processing in Dense Forest Areas using Unmanned Aerial System (UAS). Michigan Technological University, September 2022. http://dx.doi.org/10.37099/mtu.dc.michigantech-p/16366.

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Imagery collected via Unmanned Aerial System (UAS) platforms has become popular in recent years due to improvements in a Digital Single-Lens Reflex (DSLR) camera (centimeter and sub-centimeter), lower operation costs as compared to human piloted aircraft, and the ability to collect data over areas with limited ground access. Many different application (e.g., forestry, agriculture, geology, archaeology) are already using and utilizing the advantages of UAS data. Although, there are numerous UAS image processing workflows, for each application the approach can be different. In this study, we developed a processing workflow of UAS imagery collected in a dense forest (e.g., coniferous/deciduous forest and contiguous wetlands) area allowing users to process large datasets with acceptable mosaicking and georeferencing errors. Imagery was acquired with near-infrared (NIR) and red, green, blue (RGB) cameras with no ground control points. Image quality of two different UAS collection platforms were observed. Agisoft Metashape, a photogrammetric suite, which uses SfM (Structure from Motion) techniques, was used to process the imagery. The results showed that an UAS having a consumer grade Global Navigation Satellite System (GNSS) onboard had better image alignment than an UAS with lower quality GNSS.
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Lasko, Kristofer, and Sean Griffin. Monitoring Ecological Restoration with Imagery Tools (MERIT) : Python-based decision support tools integrated into ArcGIS for satellite and UAS image processing, analysis, and classification. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40262.

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Monitoring the impacts of ecosystem restoration strategies requires both short-term and long-term land surface monitoring. The combined use of unmanned aerial systems (UAS) and satellite imagery enable effective landscape and natural resource management. However, processing, analyzing, and creating derivative imagery products can be time consuming, manually intensive, and cost prohibitive. In order to provide fast, accurate, and standardized UAS and satellite imagery processing, we have developed a suite of easy-to-use tools integrated into the graphical user interface (GUI) of ArcMap and ArcGIS Pro as well as open-source solutions using NodeOpenDroneMap. We built the Monitoring Ecological Restoration with Imagery Tools (MERIT) using Python and leveraging third-party libraries and open-source software capabilities typically unavailable within ArcGIS. MERIT will save US Army Corps of Engineers (USACE) districts significant time in data acquisition, processing, and analysis by allowing a user to move from image acquisition and preprocessing to a final output for decision-making with one application. Although we designed MERIT for use in wetlands research, many tools have regional or global relevancy for a variety of environmental monitoring initiatives.
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Patwa, B., P. L. St-Charles, G. Bellefleur, and B. Rousseau. Predictive models for first arrivals on seismic reflection data, Manitoba, New Brunswick, and Ontario. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329758.

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First arrivals are the primary waves picked and analyzed by seismologists to infer properties of the subsurface. Here we try to solve a problem in a small subsection of the seismic processing workflow: first break picking of seismic reflection data. We formulate this problem as an image segmentation task. Data is preprocessed, cleaned from outliers and extrapolated to make the training of deep learning models feasible. We use Fully Convolutional Networks (specifically UNets) to train initial models and explore their performance with losses, layer depths, and the number of classes. We propose to use residual connections to improve each UNet block and residual paths to solve the semantic gap between UNet encoder and decoder which improves the performance of the model. Adding spatial information as an extra channel helped increase the RMSE performance of the first break predictions. Other techniques like data augmentation, multitask loss, and normalization methods, were further explored to evaluate model improvement.
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Schoening, Timm. OceanCV. GEOMAR, 2022. http://dx.doi.org/10.3289/sw_5_2022.

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OceanCV provides computer vision algorithms and tools for underwater image analysis. This includes image processing, pattern recognition, machine learning and geometric algorithms but also functionality for navigation data processing, data provenance etc.
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Varastehpour, Soheil, Hamid Sharifzadeh, and Iman Ardekani. A Comprehensive Review of Deep Learning Algorithms. Unitec ePress, 2021. http://dx.doi.org/10.34074/ocds.092.

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Deep learning algorithms are a subset of machine learning algorithms that aim to explore several levels of the distributed representations from the input data. Recently, many deep learning algorithms have been proposed to solve traditional artificial intelligence problems. In this review paper, some of the up-to-date algorithms of this topic in the field of computer vision and image processing are reviewed. Following this, a brief overview of several different deep learning methods and their recent developments are discussed.
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Burks, Thomas F., Victor Alchanatis, and Warren Dixon. Enhancement of Sensing Technologies for Selective Tree Fruit Identification and Targeting in Robotic Harvesting Systems. United States Department of Agriculture, October 2009. http://dx.doi.org/10.32747/2009.7591739.bard.

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The proposed project aims to enhance tree fruit identification and targeting for robotic harvesting through the selection of appropriate sensor technology, sensor fusion, and visual servo-control approaches. These technologies will be applicable for apple, orange and grapefruit harvest, although specific sensor wavelengths may vary. The primary challenges are fruit occlusion, light variability, peel color variation with maturity, range to target, and computational requirements of image processing algorithms. There are four major development tasks in original three-year proposed study. First, spectral characteristics in the VIS/NIR (0.4-1.0 micron) will be used in conjunction with thermal data to provide accurate and robust detection of fruit in the tree canopy. Hyper-spectral image pairs will be combined to provide automatic stereo matching for accurate 3D position. Secondly, VIS/NIR/FIR (0.4-15.0 micron) spectral sensor technology will be evaluated for potential in-field on-the-tree grading of surface defect, maturity and size for selective fruit harvest. Thirdly, new adaptive Lyapunov-basedHBVS (homography-based visual servo) methods to compensate for camera uncertainty, distortion effects, and provide range to target from a single camera will be developed, simulated, and implemented on a camera testbed to prove concept. HBVS methods coupled with imagespace navigation will be implemented to provide robust target tracking. And finally, harvesting test will be conducted on the developed technologies using the University of Florida harvesting manipulator test bed. During the course of the project it was determined that the second objective was overly ambitious for the project period and effort was directed toward the other objectives. The results reflect the synergistic efforts of the three principals. The USA team has focused on citrus based approaches while the Israeli counterpart has focused on apples. The USA team has improved visual servo control through the use of a statistical-based range estimate and homography. The results have been promising as long as the target is visible. In addition, the USA team has developed improved fruit detection algorithms that are robust under light variation and can localize fruit centers for partially occluded fruit. Additionally, algorithms have been developed to fuse thermal and visible spectrum image prior to segmentation in order to evaluate the potential improvements in fruit detection. Lastly, the USA team has developed a multispectral detection approach which demonstrated fruit detection levels above 90% of non-occluded fruit. The Israel team has focused on image registration and statistical based fruit detection with post-segmentation fusion. The results of all programs have shown significant progress with increased levels of fruit detection over prior art.
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