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Remote Sensing - a tool for environmental observation

Examples of digital filters are the low pass filter

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Unformatted text preview: Examples of digital filters are the low pass filter aiming at image smoothing, the high pass filter aiming at image sharpening, the gradient filter aiming at enhancing edges or transition zones in the image, the Laplace 72 filter and the Sobel filter both also aiming at enhancing edges and suppressing noise. More complex filters assess e.g. the variability of spectral reflectance in the template (texture filter, variance filters or fractal filters). A thorough description of image digital image filtering and other digital image processing techniques is given by Gonzalez and Wintz (1987). Table 5.1 shows the templates of a number of digital filters, figure 5.11 illustrates the effect of some digital filters on a simple digital profile of an image. Figure 5.10 Principle of contrast stretch enhancement (Lillesand & Kiefer, 1994). 73 Figure 5.11 The effect of a number of digital filter on the profile of a digital image. 74------------------------------------------------------------ │ 1 1 1 │ Low pass filter: 1/9 * │ 1 1 1 │ │ 1 1 1 │ │-1 -1 -1 │ High pass filter: │-1 8 -1 │ │-1 -1 -1 │ │ 0 0 │ Gradient filter: │-1 0 -1 │ │ 0 0 │ │ 0 -1 │ Laplace filter: │-1 4 -1 │ │ 0 -1 │ │ 0 -1 │ Laplace + original: │-1 5 -1 │ │ 0 -1 │ │ v1 v4 v7 │ Median filter: │ v2 v5 v8 │ │ v3 v6 v9 │ │ 1 1 1 │ Directional filter: 1/f * │ 0 0 0 │ │ 1 1 1 │------------------------------------------------------------ Table 5.1 Some examples of digital image filters. 5.7 Spectral Ratioing Spectral ratioing refers to enhancement techniques by combining pixel values from different spectral bands. Ratio images are prepared by dividing the digital numbers in one band by the corresponding digital numbers in another band for each pixel, stretching the resulting values, and plotting the new values as an image. The most widely used ratio techniques are ratios to enhance the vegetation cover or to distinguish bare soil from vegetation . Spectral indices used for these purposes are e.g. (Huete, 1989; Sellers, 1989; Tucker, 1979), the VI: Vegetation Index, the NDVI: Normalized Difference Vegetation Index , the GEMI, the SAVI: Soil Adjusted Vegetation Index, the PVI: Perpendicular Vegetation Index, the GVI: Green Vegeta- tion Index, or the TVI: Transformed Vegetation Index. Figure 1.9 and figure 5.12 illustrates the principle of the vegetation indices. Most vegetation indices combine one infrared spectral band with one visible band. 75 Vegetation indices are often used to estimate from remote sensing images the leaf area index, the vegetation cover or the biomass for specific areas (De Jong 1994; Huete, 1989). Although there is a correlation between biomass, leaf area index, vegetation cover and spectral vegetation indices, some caution is necessary. The relations between spectral indices and these vegetation properties is often area-specific (that means that functions developed in one study area cannot be used directly in other areas), the condition of the soil and the type of soil beneath the vegetation...
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Examples of digital filters are the low pass filter aiming...

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