10.10 Texture Analysis

10.10 Texture Analysis

Texture is a combination of repeated patterns with a regular frequency. In visual interpretation texture has several types, for example, smooth, fine, coarse etc., which are often used in the classification of forest types. Texture analysis is defined as the classification or segmentation of textural features with respect to the shape of a small element, density and direction of regularity.

Figure 10.10.1 (a) shows two different textures of density, while Figure 10.10.1 (b) shows two different textures with respect to the shape of the elements.

In the case of digital image, it is difficult to treat the texture mathematically because texture cannot be standardized quantitatively and the data volume is so huge.

However texture analysis has been made with statistical features which are combined with spectral data for improving land cover classification. Power spectrum analysis is another form of textural analysis in which direction and wavelength or frequency can be determined for regular patterns of , for example, sea waves and sand waves in the desert.

a. Use of Statistical Features
The following statistical values of an n x n window can be used as textural information

(1) Gray level histogram
(2) Variance - co-variance matrix
(3) Run-length matrix

These values are used for classification together with the spectral data.Figure 10.10.2 (a) shows the land cover classification using only spectral data while Figure 10.10.2 (b) shows the result of classification with spectral data as well as textural information. The result shows a better classification for the urban area which has a higher frequency and variance of image density.

b. Analysis using Power Spectrum
Power spectrum analysis is useful for those images which have regular wave patterns with a constant interval, such as glitter image of the sea surface or wave patterns of sand dunes. Fourier transformation is applied to determine the power spectrum which gives the frequency and direction of the pattern.