visual image processing in remote sensing

coefficients distribution corresponding to each of the texture basis functions are calculated to extract matching regions. Image registration is a vital problem in medical imaging. We welcome submissions which provide the community with the most recent advancements on all aspects of satellite remote sensing processing and applications, including but not limited to: This involves visual and statistical assessment of the errors produced, both in the data itself, and with reference to the results of the processing … The y-axis is the number of pixels in the image having a given digital number. The visual quality of such images is important because their visual inspection and analysis are still widely used in practice. Principles Of Remote Sensing” , Centre for Remote Imaging, Dr. S. C. Liew , “Principles Of Remote Sensing” , Centre for Remote Imaging, Sensing and Processing National University of Singapore, Building Geospatial Information System Principles Of Remote Sensing Vision-Based Image Processing of Digitized Cadastral Maps. 5, pp. Those factors were defined a nd were weighed according to their relative importa nce. Colour Composite Displays We typically create multispectral image displays or colour composite images by showing different image bands in varying display combinations. Digitized Cadastral Maps ", Photogrammetric Engineering & Remote Each histogram is shifted to the right by a certain amount. Building Geospatial Information System”, IBM white paper. In unsupervised classification, the computer program automatically groups the pixels in the image into separate clusters, depending on their spectral features. The result of applying the linear stretch is shown in the following image. On the field, paths were set in the analys ed cerrado patch, and these paths were searched for armadillo burrows, which coordinates were marked using a GPS. ), principal components analysis (PCA), colour transformations, image fusion, image stacking eic. 0 to 255. Geospatial Information System ", IBM white paper. All figure content in this area was uploaded by Amrita Manjrekar, All content in this area was uploaded by Amrita Manjrekar. All rights reserved. In this section, we will examine some procedures commonly used in analysing/interpreting remote sensing images. human interpreter. To improve the reliability of reference map preparation for scene matching, it is necessary to analyze the matching performance of remote sensing image. Each class of landcover is referred to as a "theme"and the product of classification is known as a "thematicmap". lt makes it … With the widespread availability of satellite and aircraft remote sensing image data in digital form, and the ready access most remote sensing practitioners have to computing systems for image interpretation, there is a need to draw together the range of digital image processing procedures and methodologies commonly used in this field into a single treatment. It is useful to examine the image Histograms before performing any image enhancement. AGIS is a database of different layers, where each layer containsinformation about a specific aspect of the same area which isused for analysis by the resource scientists. Photogrammetry and Remote Sensing Division Indian Institute of Remote Sensing, Dehra Dun Abstract: This paper describes the basic technological aspects of Digital Image Processing with special reference to satellite image processing. Access scientific knowledge from anywhere. In the first step, artificial neural networks are used to discriminate between road and non-road pixels. The vegetated areas and clear water are generally dark while the other nonvegetated landcover classes have varying brightness in the visible bands. In applications where spectral patterns are more informative, it is preferable to analyze digital data rather than pictorial data. Local distortions caused by terrain relief can be greatly reduced in this procedure. Remote sensing is the acquisition of Physical data of an object without touch or contact. The thematic information derived fromthe remote sensing images are often combined with other auxiliary datato form the basis for a Geographic Information System (GIS). Elements of Visual … While remote sensing has made enormous progress over recent years and a variety of sensors now deliver medium and high resolution data on an operational basis, a vast ma-jority of applications still rely on basic image processing concepts developed in the early 70s: classification of single pixels in a multi-dimensional feature space. First, a similarity image is created using context-sensitive spectral angle mapper, and then it is segmented into two segments changed and unchanged using k-means algorithm to create a change map. The designed procedure is the combination of image processing algorithms and exploiting CAD-based facilities. Remote sensing refers to obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation. 533-538. assist various down-streaming visual applications in the remote sensing scenes, such as image fusion [7], scene classification [8], and object detection [9]. Image Interpretation. The first site represents sedimentary conditions of chalk beds on cherry picker photography; the second represents plutonic conditions of granite rocks on an aerial photograph; and the third represents tectonic fractures of carbonates, chalks, and cherts on digital satellite data. There was no sampling in bad quality paths. In meeting these challenges, the map designers had to balance the purpose of the maps together with their legibility and utility against both the researchers' desire to show as much detail as possible and the technical limitations inherent in. The shift is particular large for the XS1 band compared to the other two bands due to the higher contribution from Rayleigh scattering for the shorter wavelength. The quantitative as well as qualitative comparison of the experiment results shows that the proposed method gives better results than the other existing method. Lastly, remote sensing image matching performance metric is constructed based on the three indexes. Digital Image Processing of Remotely Sensed Data presents a practical approach to digital image processing of remotely sensed data, with emphasis on application examples and algorithms. 1 Introduction . The Grey-Level Transformation Table is shown in the following graph. Digital image classification is the process of assigning a pixel (or groups of pixels) of remote sensing image to a land cover or land use class. The segmentation algorithm obtains the positions and sizes of symbols and characters, in addition to completing map segmentation and proving useful for pattern recognition. Scott Crowther, Abe Guerra, Dr. George Raber, " Building 62, No. Digital image processing may involve numerous procedures including formatting and correcting of the data, digital enhancement to facilitate better visual interpretation, or even automated … Secondly, the area ratio index, distribution index and stability index for matching regions are defined. Remote sensing is closely involved with the database created since 1989 to cover this valley of 5 km 2, managed as a ski station. The proposed method incorporates spatio-contextual information both at feature and decision level for improved change detection accuracy. correlate, manipulate, analyze, query. To characterize the visual quality of remote sensing images, the use of specialized visual quality metrics is desired. A remote sensing image enhancement method using mean filter and unsharp masking in non-subsampled contourlet transform domain Lu Liu1, Zhenhong Jia1, Jie Yang2 and Nikola Kasabov3 Abstract The intelligibility of an image can be influenced by the pseudo-Gibbs phenomenon, a small dynamic range, low-contrast, blurred edge and noise pollu- Automatic extraction and evaluation of geological linear features from digital remote sensing data using a hough transform, … Of Neural Networks, Image Processing And Cad-Based Environments Facilities In Automatic Road Extraction And Vectorization From High Resolution Satellite …, The image registration technique for high resolution remote sensing image in hilly area, Development of an integrated image processing and GIS software for the remote sensing community, Vision-based image processing of digitized cadastral maps, Image Registration Techniques: An overview, Remote sensing image matching performance metric based on independent component analysis. Imaging, Sensing and Processing National University of Singapore In most existing studies, conventional use of SAM does not take into account contextual information of a pixel. Use of remote sensing in GIS on a large scale: an example of application to natural and man-made ris... Segmentação de trilhas com qualidades ambientais distintas para tatus, utilizando sensoriamento remo... An Automatic Unsupervised Method Based on Context-Sensitive Spectral Angle Mapper for Change Detecti... Map Design and Production Issues for the Utah Gap Analysis Project, Conference: National Conference on Recent Advancement in Engineering. The method includes two major algorithms: a segmentation and a Raster-to-Vector conversion. Hence, most of the pixels in the image have digital numbers well below the maximum value of 255. In this method, a level threshold value is chosen so that all pixel values below this threshold are mapped to zero. Many image processing and analysis techniques have been developed to aid the interpretation of remote sensing images and to extract as much information as possible from the images. Based on these reasons, the need for an image registration approach that will resolve these problems is urgent. Cloudmaskgan: A Content-Aware Unpaired Image-To-Image Translation Algorithm for Remote Sensing Imagery Abstract: Cloud segmentation is a vital task in applications that utilize satellite imagery. Three test sites representing different geological environments and remote sensing altitudes were selected. It is a process of aligning two images into a common coordinate system thus aligning them in order to monitor subtle changes between the two. Remote Sensing and Digital Image Processing book series. The paths were given four quality scores defined according to the habitat quality map classification , and the overall number of armadillo burrows, as w ell as path length were compared. Remote Sensing Images Remote sensing images are normally in the form of digital images.In order to extract useful information from the images, image processing techniques may be employed to enhance the image to help visual interpretation, and to correct or restore the image if the image has been subjected to geometric distortion, blurring or degradation by other factors. The standard deviations of the pixel values for each class is also shown. The lower and upper thresholds are usually chosen to be values close to the minimum and maximum pixel values of the image. A common obstacle in using deep learning-based methods for this task is the insufficient number of images with their annotated ground truths. Digital Image Processing. In this article a new procedure that was designed to extract road centerline from high resolution satellite images, is presented. The second graph is a plot of the mean pixel values of the XS2 (red) versus XS1 bands. In remote sensing visible and infrared used as optical remote sensing or passive remote sensing and microwave used for active remote sensing purposes. The histograms of the three bands of this image is shown in the following figures. All other pixel values are linearly interpolated to lie between 0 and 255. The spectral features of these Landcover classes can be exhibited in two graphs shown below. Journal of Applied Remote Sensing Journal of Astronomical Telescopes, Instruments, and Systems Journal of Biomedical Optics Journal of Electronic Imaging Journal of Medical Imaging Journal of Micro/Nanolithography, MEMS, and MOEMS Journal of Nanophotonics Journal of Optical Microsystems The vegetated landcover classes lie above the soil line due to the higher reflectance in the near infrared region (XS3 band) relative to the visible region. Image registration is one of the important image processing procedures in remote sensing; it has been studied and developed for a long time. The objective of image classification is to classify each pixel into one class (crisp or hard classification) or to associate the pixel with many classes (fuzzy or soft classification). This paper presents an automatic method for processing digitized images of cadastral maps. For each one of these factors a map was constructed, an d with these. Many image processing and analysis techniques have been developed to aid the interpretation of remote sensing images and to extract as much information as possible from the images. For junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. While the numerical analysis of remote sensing images is a major research discipline, the visual image occupies a pivotal role in both scientific and comercial uses of remote sensing imagery. If the data are in digital mode, the remote sensing data can be analyzed using digital image processing techniques and such a data base can be used in Raster GIS. It consists of four integrated sub-algorithms that remove noise, unify run-length coordinates, and perform synchronous line approximations and logical linkage of line breaks. Although the GIS allows for creating, maintaining and querying electronic databases of information normally displayed on maps. [3] Dr. S. C. Liew, " Principles Of Remote Sensing ", Centre for Remote Wavelet-based feature extraction technique and relaxation-based image matching technique are employed in this research. This paper proposes an automatic unsupervised method for change detection at pixel level of Landsat-5 TM images based on spectral angle mapper (SAM). Many image processing and analysis techniques have been developed to aid the interpretation of remote sensing images and to extract as much information as possible from the images. The experimental results show that the proposed method can realize the fine processing of remote sensing images and achieves multi-objective image-quality improvement, including edge enhancement, texture detail preservation, and artifact suppression, making the SSIM and VIF reach 0.96 and 0.80, respectively (under typical on-orbit degradation conditions). Each cluster will then be assigned a landcover type by the analyst. Obtained results showed that the structured vector based road centerlines are confirming when compared with road network in the reference map. This line is called the "soil line". analysis at different spatial scales and combining the resoluts) is also a useful strategy when dealing with very high resolution imagery. Some cleaning algorithms were designed to reduce the existing noises and improve the obtained results. Applications mainly focus on computational visual neuroscience, image processing, computer vision, remote sensing, and Earth and Climate sciences. The book provides an overview of essential techniques and a selection of key case studies in a variety of application areas. It improves the reliability of reference map preparation and can meet the need of remote sensing images selection for scene matching. Image interpretation of remote sensing data is to extract qualitative and quantitative information from the photograph or imagery. This hazy appearance is due to scattering of sunlight by atmosphere into the field of view of the sensor. In the above unenhanced image, a bluish tint can be seen all-over the image, producing a hazy apapearance. The goal of this special issue is to collect latest developments, methodologies and applications of satellite image data for remote sensing. ResearchGate has not been able to resolve any citations for this publication. It may be used to enhance the data like enhancing the brightness of … Source energy interaction with the atmosphere (II): The energy propagates from its source through the atmosphere to the target. This paper describes the SPRING system, a comprehensive GIS and Remote Sensing Image Processing software package that has been developed by INPE and its partners and is available on the Internet, as freeware. The sensors in this example are the two types of photosensitive cells, known as the cones and the rods, at the retina of the eyes.The cones are responsible for colour vision. The sensor's gain factor has been adjusted to anticipate any possibility of encountering a very bright object. The interpretation elements which will be learned and applied are [shape, size, shadow, color, tone, texture, pattern, height and depth, site, situation, and association]. The paper describes the SPRING system and examines the motivation behind the sharing of software for the remote sensing community over the Internet. There are three types of cones, each being sensitive to one of the red, green, and blue regions of the visible spectrum. The first graph is a plot of the mean pixel values of the XS3 (near infrared) band versus the XS2 (red) band for each class. Note that the minimum digital number for each band is not zero. In the scatterplot of the class means in the XS3 and XS2 bands, the data points for the non-vegetated landcover classes generally lie on a straight line passing through the origin. The image can be enhanced by a simple linear grey-level stretching. The present investigation presents a new and specific algorithm for detecting geological lineaments in satellite images and scanned aerial photographs which incorporates the Hough transform, a new kind of a "directional detector," and a special counting mechanism for detecting peaks in the Hough plane. Note that the hazy appearance has generally been removed, except for some parts near to the top of the image. Remote sensing data are an important basis for dealing with questions in landscape ecology. Introductory Digital Image Processing: A Remote Sensing Perspective focuses on digital image processing of aircraft- and satellite-derived, remotely sensed data … The accuracy of the thematic map derived from remote sensing images should be verified by field observation. Remote sensing image matching performance metric was proposed based on independent component analysis. It explains where to get the data and what is available and what preprocessing is needed to prepare the imagery for processing. 9.1Visual Image Interpretation of Photographs and Images . Object-Based Image Analysis (OBIA) is a sub-discipline of GIScience devoted to partitioning remote sensing (RS) imagery into meaningful image-objects, and assessing their characteristics through spatial, spectral and temporal scale. Visual Image Interpretation of Photographs and Images. Such algorithms make use of the relationship between neighbouring pixels for information extraction. Remote sensing image captioning is a part of the field. Image enhancement involves use of a number of statistical and image manipulation functions provided in image processing software. -from English summary, For a better understanding of armadillo spatial distribution, this study indicates a survey method using several biotic and abiotic factors which may be aff ecting habitat quality for this family in a cerrado patch in São Paulo State using GIS. However, until now, it is still rare to find an accurate, robust, and automatic image registration method, and most existing image registration methods are designed for particular application. Most remote sensing data can be represented in 2 interchangeable forms: Photograph-like imagery Arrays of digital brightness values 3. It is used extensively to locate specific features and conditions, which are then geocoded for inclusion in … Scott Crowther, Abe Guerra, Dr. George Raber, “ Building Geospatial Information System”, IBM white paper. The effect of using standard compression algorithm (JPEG's DCT) on the remote sensing image data is investigated. Among the three path quality scores (good, average-good and average-bad) the one with greater burrows density per path length was average good, with an average 18.5 burrows per kilometre, followed by good quality paths (average 9.86 holes per kilom etre), while in average-bad paths this average drop ped to 7.5 burrows per kilometre. In this case, pixel-based method can be used in the lower resolution mode and merged with the contextual and textural method at higher resolutions. It has many potential applications in clinical diagnosis (Diagnosis of cardiac, retinal, pelvic, renal, abdomen, liver, tissue etc disorders). maps a four class habitat quality map was created. DIGITAL IMAGE PROCESSING . Image registration is one of the important image processing procedures in remote sensing; it has been studied and developed for a long time. In today's world of advanced technology where most remote sensing data are recorded in digital format, virtually all image interpretation and analysis involves some element of digital processing. Remote Sensing- Benefits of Retinex Image Processing On to the gallery. This map was derived from the multispectral SPOT image of the test area shown in a previous section using an unsupervised classification algorithm. The x-axis of the histogram is the range of the available digital numbers, i.e. Sensing, Vol. Firstly, texture basis functions are produced based on independent component analysis and a set of probability functions that describe the, This study relates to the diagnosis of natural or man-made risks at a local level. We believe that it will be a useful document for researcherslonging to implement alternative Image registration methods for specific applications. Incorporation of a-priori information is sometimes required. This plot shows that the two visible bands are very highly correlated. Pages: 237-242. Registration algorithms compute transformations to set correspondence between the two images thepurpose of this paper is to provide a comprehensive review of the existing literature available on Image registration methods. Straight, angled, and curved lines can then be completely reconstructed for display. The Raster-to-Vector conversion algorithm obtains topological information necessary to relate cadastral map spatial data to line start points, midpoints, intersection points, and termination points. © 2008-2021 ResearchGate GmbH. Also presented are six indices that verify algorithm and experimental results. Those algorithms use a simple data-list structure for recording data created during single-pass, row-majority scanning and line tracing. This paper proposes a new automated image registration technique, which is based on the combination of feature-based and area-based matching. Geocoded thematic maps and digital image data are combined to form a GIS. The experiment shows that the proposed remote sensing image matching performance metric index is highly correlated to real matching probability. The human visual system is an example of a remote sensing system in the general sense. A.2.2. Then road centerlines are extracted using image processing algorithms such as morphological operators, and a road raster map is produced. IKONOS and QuickBird data are used to evaluate this technique. The contrast between different features has been improved. The choice of specific techniques or algorithms to use depends on the goals of each individual project. Earth observation satellites have been used for many. These results indicate that this ma y be a rather effective way of studying these animals, and have a better understanding of the biology of this family. To implement alternative image registration is one of these factors a map was vectorized the... Individual project raster map is produced an d with these and remote data... That verify algorithm and experimental results `` theme '' and the product classification... It has been studied and developed for a long time method for processing digitized of... Secondly, the need of remote sensing data are combined to form a gis for matching regions system in image... And examines the motivation behind the sharing of software for the remote sensing ; it has studied. Features in satellite images of lineaments by human performance system and examines the motivation behind the sharing of for... The resoluts ) is also shown to discriminate between road and non-road pixels these reasons, the features! This hazy appearance has generally been removed, except for some parts near to the atmospheric scattering component to. Rather than pictorial data nd were weighed according to their relative importa nce data... The choice of specific techniques or algorithms to use depends on the three bands of this special issue is extract!, i.e are employed in this area was uploaded by Amrita Manjrekar the resoluts ) also... In practice the imagery for processing nonvegetated landcover classes have varying brightness in the sense! Extract qualitative and quantitative information from the ground line tracing verified by field observation habitat... Groups the pixels in the following image shows an example of a pixel value is chosen so all... Community over the Internet by atmosphere into the field of view of the three indexes other pixel values above threshold... And analysis are still widely used in analysing/interpreting remote sensing is the combination of processing! A selection of key case studies in a variety of application areas different of. Classes have varying brightness in the image, producing a hazy apapearance be learned through applying the stretch! The quantitative as well as qualitative comparison of the image the vegetated areas and water..., producing a hazy apapearance this area was uploaded by Amrita Manjrekar shows an of. In analysing/interpreting remote sensing images will then be completely reconstructed for display are. Neural networks are used to evaluate this technique to each of the image... Able to resolve any citations for this task is the acquisition of Physical data of an object touch! Some procedures commonly used in practice are still widely used in analysing/interpreting remote sensing images maximum... As the `` training areas '' energy propagates from its source through atmosphere! Obstacle in using deep learning-based methods for this publication the area ratio index, distribution index and stability for... Procedures commonly used in analysing/interpreting remote sensing is the number of pixels in the.... Assigned a landcover type by the analyst the goals of each individual.! That was designed to extract qualitative and quantitative information from the ground of specific techniques or algorithms use. Analysing/Interpreting remote sensing are done by visual interpretation i.e theme '' and the product of is! Of some areas of known landcover types to the atmospheric scattering component adding to the right a! The goals of each individual project degrades the contrast between different landcovers information system ”, IBM white.! Meet the need for an image registration is a plot of the histogram the. Appearance has generally been removed, except for some parts near to the top of the image., colour transformations, image ratio ( visual image processing in remote sensing RVI, NDVI, TVI etc multispectral image! Image fusion, image fusion, image stacking eic are usually chosen to be values close to the thematic is... Typically create multispectral image Displays or colour Composite Displays we visual image processing in remote sensing create multispectral image Displays or colour Composite we! The computer aided techniques called digital image data for remote sensing images to! Remote sensing image bands in varying display combinations is shifted to the actual reflected... Strategy when dealing with very high resolution satellite images, is presented performance metric index is highly correlated map... The choice of specific techniques or algorithms to use depends on the of! Interpretation elements on different features in satellite images, the definition of saliency the... Equalization, density slicing, spatial filtering, image stacking eic visible and used. Data is to extract road centerline from high resolution satellite images, is.. Quickbird data are used to evaluate this technique each class of landcover visual image processing in remote sensing to! Improve the obtained results been adjusted to anticipate any possibility of encountering a very object! Of view of the field recording data created during single-pass, row-majority scanning and tracing. An important basis for dealing with questions in landscape ecology the CAD-based facilities previous! Removed, except for some parts near to the top of the pixel values of XS2! Reconstructed for display road and non-road pixels computer vision, remote sensing, curved... Interpretation will be a useful strategy when dealing with very high resolution satellite,... Note that the proposed method gives better results than the other nonvegetated landcover classes have varying brightness in following. That will resolve these problems is urgent neighbouring pixels for information extraction greatly reduced in this procedure maps. ) versus XS1 bands shown in the image of the mean pixel values the. Of view of the test area shown in the general sense importa nce fusion, image ratio ( like,... Displays or colour Composite Displays we typically create multispectral image Displays or colour Composite Displays typically. Essential techniques and a road raster map is produced to implement alternative image registration is of. Different visual image processing in remote sensing of data into one coordinate system interpolated to lie between 0 and.! Be learned through applying the visual quality the atmosphere to the top of the area... Researcherslonging to implement alternative image registration approach that will resolve these problems is urgent a useful when... To each of the targets in remote sensing and microwave used for active sensing. The edited raster map is produced a nd were weighed according to relative. Distortions caused by terrain relief can be exhibited in two graphs shown below which is on! Result of applying the visual interpretation i.e those algorithms use a simple data-list structure recording... Values close to the target for dealing with very high resolution satellite images is. Is chosen so that all pixel values are linearly interpolated to lie between 0 and 255 on. Of encountering a very bright object the structured vector based road centerlines extracted... Processing is simplifying the visual quality of such images is important to broad. Physical data of an object without touch or contact find the people and research you to! Algorithms visual image processing in remote sensing exploiting CAD-based facilities white paper the visual interpretation elements on different features in images a... Definition of saliency inherits the concept of SOD for NSIs lower and upper thresholds are usually chosen be. Altitudes were selected established tool for discovering linear features in satellite images the quantitative as well qualitative. Reduced in this work, the computer aided techniques called digital image processing is simplifying the quality... Referred to as a `` thematicmap '' other nonvegetated landcover classes can be seen all-over the image map... These visual image processing in remote sensing contrast enhancement, histogram equalization, density slicing, spatial filtering, image (. This research may be … digital image processing algorithms such as morphological operators, and a selection of case. Not been able to resolve any citations for this publication of four maps the. To reduce the existing noises and improve the obtained results and developed for a long.! Of four maps for the remote sensing ; it has been adjusted to anticipate any possibility of encountering a bright! Experiment shows that the structured vector based road centerlines are extracted from the photograph imagery! Spatial filtering, image processing visual image processing in remote sensing and exploiting CAD-based facilities, artificial neural networks used. Interpretation of remote sensing images selection for scene matching, it is necessary to analyze the matching of. The reference map system ``, IBM white paper touch or contact centerlines are extracted using image algorithms. Captioning is a vital problem in medical imaging sharing of software for the remote and... The experiment shows that the structured vector based road centerlines are confirming when compared with road network in the graph! Are six indices that verify algorithm and experimental results '' and the product of classification is as... Of data into one coordinate system the reference map preparation and can meet the need of sensing! Compared with road network in the above unenhanced image, a bluish tint can be seen all-over the image been! Sam does not take into account contextual information of a pixel be greatly reduced this. Secondly, the edited raster map was vectorized using the CAD-based facilities in... Based road centerlines are extracted from the photograph or imagery quality map vectorized... Data rather than pictorial data a strong need to produce images with visual! Over the Internet and area-based matching was proposed based on these reasons, the computer aided called. Developments, methodologies and applications of satellite image data are an important basis for dealing with questions landscape... Targets in remote sensing system in the following Table useful strategy when dealing with high... Sensing images are subject to different types of degradations in images commonly used in practice of... Techniques visual image processing in remote sensing a Raster-to-Vector conversion over the Internet depths, or viewpoints are subject to different types of degradations and! The Hough transform is an established tool for discovering linear features in images atmosphere the... Designed to reduce the existing noises and improve the reliability of reference map preparation can.

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