According to the difference of spectral characteristics between mineralized altered rocks and surrounding rocks, the image variables with enhanced mineralized altered information are obtained through image enhancement processing, and finally the purpose of extracting mineralized altered information is realized.
There are several ways to enhance the prominent alteration information in general images:
(1) band combination operation
Band addition and subtraction combination operation can enlarge the difference of brightness values between bands. Comparing the spectral curves of mineralized altered rocks and surrounding rocks (Figure 6-2), we can see that the spectral curves of mineralized altered rocks fluctuate greatly, that is to say, there are great differences between bands; On the contrary, the spectral curve of surrounding rock is relatively flat, indicating that the difference between bands is small. According to this feature, the brightness difference between mineralized altered rocks and surrounding rocks can be amplified by using the combined operation of band addition and subtraction, thus enhancing the information of mineralized altered rocks. Mineralized altered rocks have reflection peaks in TM5 and TM3 bands, which are more different from surrounding rocks, while absorption peaks are close to surrounding rocks in TM 1, TM4 and TM7 bands. Therefore, the following operations can be adopted to reduce the interference of terrain on image information:
(TM5+TM3+TM2)-(TM7+TM4+TM 1)(6- 1)
To avoid negative values, TM2 is used as an addend.
(2) Frequency band ratio
Band ratio method is based on the principle of algebraic operation When the differences between bands are similar but the slopes are different, the ratio of reflection band to absorption band is used to enhance the spectral differences between various lithology, suppress the influence of topography and display the dynamic range. Therefore, based on the characteristic spectra of minerals, selecting the appropriate band ratio for color synthesis can enhance the weak information. For altered minerals, it is to analyze the spectral curve of altered minerals, find out the interval with the largest slope change and the reflection peak and absorption valley in the curve, determine the spectral range, enhance the ratio, and form an image that highlights the alteration information. General calculation formula of ratio:
DN’ls = a(DNils/DNjls)+b(6-2)
Where: dn'ls is the ratio of luminance values of L rows and S columns of pixels in band I and band J; A and b are two constants for adjusting the dynamic range of the ratio.
According to the field spectral measurement, there are three types of altered minerals that can be identified theoretically by TM image data: ① Iron oxides, hydroxides and sulfates, including limonite, hematite, goethite and jarosite, which have great rising gradients in the spectral reflectance curves of TM 1, TM2 and TM3 bands, but have strong spectral absorption bands near TM4 bands; ② The typical characteristics of the reflection spectrum of hydroxyl minerals (including clay minerals and mica) are strong spectral absorption in TM7 band; ③ Hydrated sulfate minerals (gypsum and alunite) and sulfate minerals (calcite and dolomite) have strong spectral absorption in TM7 band.
The band ratio commonly used to identify hydrothermal alteration is TM3/TM 1, which is used to identify limonite. TM5/TM4 is used to distinguish between vegetated and vegetated soils and rocks, mica and jarosite, alunite and gypsum, calcite and clay, and to identify limonitization; TM5/TM7 can identify hydroxyl-containing minerals, hydrated sulfates and carbonates.
(3) Principal component analysis
Principal component analysis (PCA), commonly called KL transform in mathematics, is a widely used method to extract rock alteration information. This method is the concentration and compression of image data, which concentrates the highly relevant information of each band in multi-spectral images into several bands and ensures that the information of these bands is as irrelevant as possible. That is, several comprehensive bands are used to represent the multi-band original image, which reduces the amount of data processed. For TM images, PC 1, PC2 and PC3 usually contain more than 95% information. Its operation mode is shown in Figure 6-3.
Principal component analysis (PCA) uses linear transformation method to achieve decorrelation based on the relationship between variables under the premise of complete information conservation. Because the obtained principal components are irrelevant, the information between the principal components is not repeated or redundant. The extraction of alteration anomaly information makes use of this basic property of principal component analysis. Each principal component of TM multi-band data obtained by PCA often represents a certain geological significance and does not repeat each other, that is, the geological significance of each principal component has its uniqueness.
Principal component analysis is a classical and widely used method to extract rock alteration information. Iron components, OH- and alteration information are extracted by two groups of principal component analysis (TM 1, TM3, TM4, TM5) and (TM 1, TM4, TM5, TM7).
Figure 6-3 Principal Component Analysis Model
PCA is conducted in four bands: TM 1, TM3, TM4 and TM5. The criterion for judging the principal component of iron spot is that the TM3 coefficient of the feature vector of this principal component should be opposite to that of TM 1 and TM4, and the sign of TM3 is generally the same as that of TM5 coefficient. According to the spectral characteristics of related ground objects, iron staining information is included in the principal components that meet this criterion, which is called iron staining abnormal principal components. The main purpose of avoiding the simultaneous operation of TM5 and TM7 bands is to eliminate the interference of alteration information of clay minerals.
PCA is performed in four frequency bands: TM 1, TM4, TM5 and TM7. The criterion for judging the hydroxylated principal component is that the TM5 coefficient of the eigenvector of this principal component should be opposite to that of TM7 and TM4, and TM 1 is generally the same as that of TM5. According to the spectral characteristics of related ground objects, the principal component that meets the criterion contains hydroxyl information, so the principal component can be called hydroxyl abnormal principal component. TM2 and TM3 bands are deleted to prevent visible light bands from participating in the operation at the same time, mainly to eliminate the interference of iron oxide.
2. Extraction of mineralization and alteration information in the study area.
According to the spectral basis and theoretical basis of mineralization extraction, various enhanced extraction models in this study area were tested by using ERDAS8.7 remote sensing images, and finally the model with better effect was selected. The specific extraction steps are as follows.
(1) ETM+ 1, ETM+3, ETM+4 and ETM+5 are used as principal components to extract the "iron group diagram".
The characteristic spectral information of iron oxides is concentrated in ETM+ 1 ~ 4 band, with absorption peaks in ETM+4 and ETM+ 1 band, and no characteristic absorption in TM3 band, showing relatively high reflection. Among the four PC images obtained by principal component analysis, the PC with the strongest iron information is the PC with the largest load factors of ETM+3 and ETM+ 1, and the numerical signs of the load factors are opposite, which is called "iron group image". Therefore, PC4 is finally selected as the iron group image (Table 6-3).
Table 6-3 Eigenvectors and Eigenvalues of ETM+1,ETM+3, ETM+4 and ETM+5 bands
(2) Using ETM+ 1, ETM+4, ETM+5 and ETM+7 as main components to extract "hydroxyl diagram" (carbonation and clayey).
The characteristic spectral information of clay minerals (hydroxyl-containing minerals) is concentrated in ETM+5 and ETM+7 bands, with characteristic absorption band in ETM+7 band and relatively high reflection in ETM+5 band. The sign of ETM+5 coefficient should be opposite to that of ETM+7 and ETM+4, and the sign of ETM+ 1 is almost the same as that of ETM+5 coefficient. Therefore, PC4 was finally selected as the hydroxyl group diagram (Table 6-4).
Table 6-4 Eigenvectors and Eigenvalues of ETM+1,ETM+4, ETM+5 and ETM+7 bands
(3) color synthesis
The brightness index of the original image is very low. In order to produce a good visual effect and further explanation, the iron group diagram and hydroxyl diagram are linearly stretched and histogram equalized respectively, and finally combined with ETM+5/ETM+7 bands of R, G and B colors, and the yellow area is a mixed alteration band (see Figure 6-4).
Figure 6-4 Distribution Map of Alteration Zone in the Study Area (Yellow Mixed Alteration)
(See the chart at the back of the book for a color map.)