Geometric rectification technique for high resolution satellite data imagery using new geocentric-based datum (original) (raw)
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Precision rectification of high resolution satellite imagery without ephemeris data
International Journal of Applied Earth Observation and Geoinformation, 2001
The huge capability of high resolution satellite imageries (HRSI), that includes spatial, spectral, temporal and radiometric resolutions as well as stereoscopic vision introduces them as a powerful new source for the Photogrammetry, Remote Sensing and GIS communities. High resolution data increases the need for higher accuracy of data modeling. The satellite orbit, position, attitude angles and interior orientation parameters have to be adjusted in the geometrical model to achieve optimal accuracy with the use of a minimum number of Ground Control Points (GCPs). But most high resolution satellite vendors do not intend to publish their sensor models and ephemeris data. There is consequently a need for a range of alternative, practical approaches for extracting accurate 2D and 3D terrain information from HRSI. The flexibility and good accuracy of the alternative models demonstrated with KFA-1000 and the wellknown SPOT level 1A images. A block of eight KFA-1000 space photos in two strips with 60% longitudinal overlap and 15% lateral sidelap and SPOT image with rational function, DLT, 2D projective, polynomials, affine, conformal, multiquadric and finite element methods were used in the test. The test areas cover parts of South and West of Iran. Considering the quality of GCPs, the best result was found with the DLT method with a RMSE of 8.44 m for the KFA-1000 space photos.
Islamic University, 2016
ABSTRACT Every satellite image has some distortions that affect the geometric accuracy of these images, These distortions are classed in two groups; systematic and non-systematic distortions. The systematic distortions are corrected by applying formulas derived by modeling the source of the distortions mathematically. Non-systematic distortions, and residual unknown systematic distortions are corrected by analysis of well-distributed ground control points (GCPs) which occurring on the satellite image. The satellite images are delivered after applying some correction processes like radiometric- distortions, but some of these images must be rectified to remove the other types of distortions, so rectification processes are applied. To apply the rectification processes, it is necessary to acquire the fundamental model of the satellite and applying different mathematical models. These models relate between the point on the image and its conjugate on the earth, and using several models to give the best accuracy. For this research, a satellite image for Gaza City-Palestine was used. These 38 GCPs are collected and read which are divided to 26 control points for the rectification process and 12 control points as check points to assure the accuracy of the process. Erdas Imgaine Program was used as software at the rectification and analysis process. In general, it is found that the third order polynomial gives the best results. The effect of GCPs number on resulted accuracy was studied. The rectification operation is repeated by reducing the number of the GCPs gradually in the image. It is found that the accuracy of rectification is directly proportional with the number of GCPS.
International Journal of Digital Content Technology and its Applications, 2012
Rectification process is necessary so as to orient a satellite imagery to a planar surface and make its geometry planimetric. It establishes the image in the correct spatial location and orientation for subsequent quantitative analysis. This paper introduces the rectification of a true color Satellite imagery that was synthesized out of a Quick Bird high resolution Satellite imagery data for quantitative analysis. However an overview of the geometric correction process was also highlighted. Reference system is an important factor in order to verify and identify all measurements and data collection processes from Satellite imageries. The quality of the outputs depends on how good and refined the reference system is defined. The technique uses Global Positioning System (GPS) positioning information, geo-reference and other parameters, such as interpolation method to automatically register and ortho rectify the raw imagery data. Through the process, a seamless imagery is produced. Through semi-automatic and manual editing, a standard satellite-map imagery that satisfies geometric extraction needs was produced which would subsequently be used to determine quantitatively, geometric cadastral boundaries, hence, analyzing the imagery data. The result of the satisfactory imagery rectification shows that the total root mean square (RMS) error is 0.6152 meter, for X is 0.4119 meter and for Y is 0.4570 meter.
Analysis and quantification of errors in the geometric correction of satellite images
1985
The quantitative use of remote sensing satellite images in many applications requires that the geometric distortion inherent in these images be corrected, or rectified, to a desired map projection. The most widely used technique relies on ground control points to empirically determine a mathematical coordinate transformation to correct the geometry. In this paper, using the method of least squares, expressions for the accuracy of the geometric transformation and of the rectification of the satellite image to a map projection are derived. Explicit relations between the global accuracy of the transformation and the number, location, and local accuracy of the ground control points are obtained. The results are applied to the correction of a Landsat MSS image.
Approximate approaches to geometric corrections of high resolution satellite imagery
Geo-Spatial Information Science, 2004
The exploitation of different non-rigorous mathematical models as opposed to the satellite rigorous models is discussed for geometric corrections and topographic/thematic maps production of high-resolution satellite imagery (HRSI). Furthermore, this paper focuses on the effects of the number of GCPs and the terrain elevation difference within the area covered by the images on the obtained ground points accuracy. From the research, it is obviously found that non-rigorous orientation and triangulation models can be used successfully in most cases for 2D rectification and 3D ground points determination without a camera model or the satellite ephemeris data. In addition, the accuracy up to the sub-pixel level in plane and about one pixel in elevation can be achieved with a modest number of GCPs.
ISPRS Congress, 2004
For various satellite imagery applications, geo-referencing through rectification is a common operation. Rigorous mathematical models with the aid of satellite ephemeris data can present the relationship between the image space and object space. With government funded satellites, access to calibration and ephemeris data allowed the development of these models. However, for commercial high-resolution satellites, these data have been withheld from users, and therefore alternative empirical rectification models have been developed. In general, most of these models are based on the use of control points. The lack of control points in some remote areas such as deserts, forests and mountainous areas provides a catalyst for the development of algorithms based on other image features. One of the alternatives is to use linear features obtained from scanning/digitizing hardcopy maps, from terrestrial mobile mapping systems or from digital images. In this work, a new model named the Line Based Transformation Model (LBTM) is established for satellite imagery rectification. The model has the flexibility to either solely use linear features or use linear features and a number of control points to define the image transformation parameters. As with other empirical models, the LBTM does not require any sensor calibration or satellite ephemeris data. The underlying principle of the model is that the relationship between line segments of straight lines in the image space and the object space can be expressed by affine or conformal relationships. Synthetic as well as real data have been used to check the validity and fidelity of the model, and the results show that the LBTM performs to a level comparable with existing point based transformation models.
Applications on geometric correction of different resolution satellite images
University of Naples “ …, 2011
In Remote Sensing, because of some parameters correlated to platform instabilities, sensor geometry, curvature and rotation of Earth, satellite images are affected by geometric distortions. A part of them is often corrected directly by the providers, while the other ones can be limited referencing the images to existing maps. In fact, when remotely sensed data, such as Landsat or MODIS (Moderate Resolution Imaging Spectroradiometer) or IKONOS images, are acquired, they are represented in geometric scheme by rows and columns. As the relationship between this raster format and real plane or geographic coordinates system is missing, a georeferencing process must be realized to obtain this correlation. In this paper methods to correct satellite images and to adapt them to cartographic representations are shown and the accuracy parameters are discussed with the aim to achieve results assessment. Applications are focalized on images concerning Campania Region with low (MODIS), medium (Landsat) and high (IKONOS) resolution.
International Journal of Computer Applications, 2011
Image Processing is a technique which is used to enhance raw images received from cameras and sensors placed on satellites, space probes and aircrafts or pictures taken in normal day-today life for various applications. Remotely-sensed data obtained from satellites or aircraft are usually geometrically distorted due to the acquisition system and the movements of the platform. A geometric correction of the image is required whenever the image is to be compared with existing maps or with other images. This paper deals with the composition of a correction function using ground control points. They offer a computational advantage and simplify the analysis of significant terms in the correction function. An accuracy analysis is performed, with emphasis being laid on the number and location of the ground control points.
2005
High resolution satellite data is becoming as an indispensable data source in large scale mapping due to affordable cost and possibility of supplying data on-demand. Among currently available and most successful sources are IKONOS and QuickBird that belong to commercial agencies. Panchromatic band of QuickBird is providing 0.61 meters ground resolution that can easily be used to derive high accuracy large-scale maps from space data. Spatial accuracy of the information extracted from these high-resolution images highly depends on the accuracy of the geometric properties of images provided by vendors. Further, in most of cases users heed to carryout their own geometric correction to adjust satellite data for their respective projection and coordinate system primarily with Ground Control Point (GCP). This study evaluates the effect of GCP accuracy, distribution and the number of GCP’s in the processes of geometric correction of QuickBird data over Bangkape area of Bangkok. More than 50...