PROCESSING OF SATELLITE IMAGE USING DIGITAL IMAGE PROCESSING (original) (raw)
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Digital Image Processing of Remotely Sensed Satellite Images for Information Extraction
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The Geographic Information System is a collection of located, collected, stored and managed geographic data with the use of the computer, data which can be used to perform various spatial analyses. The special GIS operations over the spatial information make from these instruments more than just efficacy instruments for making maps, but especially, irreplaceable instruments for analyzing the information that refer to the terrestrial surfaces. GIS maps must be made exploiting all available resources based on rigorous analysis of their content and the costs involved, seeking assurance required with maximum efficiency. Each data source requires the existence of specialized programs that would bring appropriate map data into digital form, starting with providing necessary equipment, going through technological problems and data conversion, with the purpose of preparation and proper training of personnel. In a GIS, data can be stored in two fundamental spatial data models: vector and ras...
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bvicam.ac.in
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During the few years, various algorithms have been developed to extract features from the high resolution satellite imagery. For classification of these extracted features several complex algorithms have been developed. But these algorithms do not possess critical refining stages of processing the data at the preliminary phase. There are various satellite sensors that have been launched such as LISS3, IKONOS, QUICKBIRD, WORLD VIEW etc. Prior to classification and extraction of semantic data, imagery of the high resolution must be refined. The whole refinement process involves several steps of interaction with the data. These steps are preprocessing algorithms which are presented in this paper. Preprocessing steps involves Geometric correction, radiometric correction, Noise removal, Image enhancement etc. Due to these preprocessing algorithms the accuracy of the data is increased.Various applications of these preprocessing of the data is in meteorology, hydrology, soil science, forest, physical planning etc. This paper also provides a brief description of local maximum likelihood method, fuzzy method, stretch method and preprocessing methods, which are used prior to classifying and extracting features from the image.
FEATURE ISOLATION AND EXTRACTION OF SATELLITE IMAGES FOR REMOTE SENSING APPLICATIONS
Image enhancement is to improve the visual appearance of an image, or to provide a " better transform representation for future automated image processing. The reason behind image enhancement methods is to raise image visibility and aspects. Image enhancement is one of the ways as they improve the quality of the image by increasing dominance of some aspects or by decreasing uncertainty among unusual areas of the image. Image enhancement methods exist of a collected works of techniques that try to find to improve the visual appearance of an image or to convert the image to a form enhanced appropriate for investigation by anyone or any piece of tools. Several images bear from poor contrast and therefore, it is vital to enhance the contrast. Contrast enhancement is one of the most demanding concerns in low level image processing. Contrast enhancement methods are utilized for the betterment of the visual observation and colour facsimile of low contrast images. This work presents a Linear Contrast stretch and intensity level slicing technique to enhance images obtained through satellites.
A SURVAY OF DIGITAL IMAGE PROCESSING AND ITS PROBLEM
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Special Issue "Image processing and satellite imagery analysis in environments"
The Special Issue of Geosciences titled: “Image Processing and Satellite Imagery Analysis in Environments" is here proposed to stress the role of satellites in the analysis and monitoring of environments. However, satellite imagery needs to be processed to extract data from it. Many methods and algorithms exist and many can be developed which can properly enhance and extract information from satellite maps, in different ranges of frequencies, recorded at different scales, from local to global environments. Link https://www.mdpi.com/journal/geosciences/special\_issues/Image\_processing\_satellite\_environments
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The effects of spatial resolution on the satellite image properties as well as on the quality of the extracted information on Earth's surface properties using satellite data have been analysed. Two characteristically different surfaces (i) a relatively homogeneous surface area with relatively uniform distribution of surface classes (soil, vegetation and water) and (ii) a relatively heterogeneous (spatially) surface area with spatially non-uniform distribution of surface classes are extracted from an image of Landsat TM having a spatial resolution of 30 m. Using these two scenes of Landsat TM, images of different spatial resolutions ranging from 60 to 600 m have been prepared though degradation of the spatial resolution of the image by the application of an average filtering. The statistical properties of the spatially degraded images have been studied. Increasing degradation of spatial resolution of images decreases the image contrast. This degradation of spatial resolution caus...