Haralick Texture
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| + | Image texture is a quantification of the spatial variation of grey tone values. Haralick | ||
| + | et al. (1973) presented texture measures that may be derived by comparing the values | ||
| + | of the digital numbers within a window. An essential component of the concept of | ||
| + | the Haralick texture measures is the definition of eight nearest-neighbor resolution cells | ||
| + | (Fig.). Now we may define different matrices for different angles (0o,45o,90o,135o) and | ||
| + | distances between the horizontal neighboring pixels. | ||
| + | Many studies in land cover and forest type classification utilize textural features to | ||
| + | improve the classifcation accuracies. | ||
| + | We use the ASTER satellite band number 1 (green) and an inter-pixel sampling distance | ||
| + | of one. At first we need to linearly transform the 16-bit ASTER data to 8-bit radimetric | ||
| + | resolution. | ||
| + | |||
| + | {{Exercise|message=Exercise 35|text=}} | ||
[[category:Image enhancement III|4]] | [[category:Image enhancement III|4]] | ||
Revision as of 10:43, 1 November 2010
Image texture is a quantification of the spatial variation of grey tone values. Haralick et al. (1973) presented texture measures that may be derived by comparing the values of the digital numbers within a window. An essential component of the concept of the Haralick texture measures is the definition of eight nearest-neighbor resolution cells (Fig.). Now we may define different matrices for different angles (0o,45o,90o,135o) and distances between the horizontal neighboring pixels. Many studies in land cover and forest type classification utilize textural features to improve the classifcation accuracies. We use the ASTER satellite band number 1 (green) and an inter-pixel sampling distance of one. At first we need to linearly transform the 16-bit ASTER data to 8-bit radimetric resolution.
