Remotely sensed data are usually digital image data. Therefore data processing in remote sensing is dominantly treated as digital image processing.
Figure 8.1.1 shows the data flow in remote sensing. Figure 8.1.2 shows the major data processing techniques in remote sensing.
(1) Input data
There are two data sources; analog data and digital data. Digital data, for example multispectral scanner data, is converted from HDDT (high density digital tape) to CCT (computer compatible tape) for ease of computer analysis. Analog data for example, film must be digitized by an image scanner or drum scanner into digital image data.
(2) Reconstruction / Correction
Reconstruction, restoration and/or correction of radiometry and geometry should be undertaken in the process of preprocessing.
(3) Transformation
Image enhancement, spatial and geometric transformation and/or data compression is normally required to generate a thematic map or database.
(4) Classification
Image features are categorized, which is called labeling in image processing, using those techniques of learning, classification, segmentation and/or matching.
(5) Output
There are two output methods; analog output such as film or color copy, and digital output in the form of a database, which is usually used as one of the layers of geographic data in GIS (geographic information system).
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