**3.4 Image statistics**

*Applied Geochemistry with Case Studies on Geological Formations, Exploration Techniques…*

After 39 kinds of geochemical elements (or oxide) were generated, they would be put together to form an image atlas. The method is simple, namely, using "Laystacking"

From the view of spectroscopy, the geochemical elements need to be classified. In the periodic table of the elements, elements of the same family possess similar chemical properties, and they have similar enrichment characteristics in the earth. In accordance with the periodic table, the element family was arranged from left to right. In each family, the order was arranged from top to bottom. In this way, the order of the arranged geochemical elements was as follows: Li, Na2O, K2O, Be, MgO, CaO, Sr, Ba, Y, La, Th, U, Ti, Zr, V, Nb, Cr, Mo, W, Mn, Fe2O3, Co, Ni, Cu, Ag, Au, Zn, Cd, Hg, B, Al2O3, SiO2, Sn, Pb, P, As, Sb,

In ENVI software, it is very easy to form the spectra which are constituted of the results of different geochemical elements. This paper defined these spectra as geochemical spectra, which is somewhat similar to the geochemical anomaly and the geochemical chart mentioned in geochemistry, all of which imply the content of geochemical element. All the data in the element content image are with original value, which is easy for data comparisons. If only considering the characteristic of the spectrum, methods of normalization may be adopted, namely, histogram stretching was conducted on each element content image to form the numerical range from 0 to 1, thus creating a clearer and more obvious contrast geochemical spectrum. **Figure 6** shows a comparison of the spectrum of main ore deposits in the Manzhouli region. The ore deposits shown in **Figure 6** are Sanhe lead-zinc deposit, Xiahulin lead-zinc deposit, Waixinhe molybdenum deposit, Babayi copper deposit, Wunugetushan copper-molybdenum deposit, Jiawula lead-zinc deposit, Chaganbulagen lead-zinc-silver deposit, and Erentaolegai silver deposit,

command, respectively, each image was successively overlayered together.

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respectively.

**3. Results**

**Figure 5.**

Bi, and F.

**3.2 Geochemical spectrum**

**3.1 Building geochemical atlas**

*Rasterized image of Ag element after a buffer zone mask.*

Geochemical image can carry out a numerical statistics, which are somewhat different from the statistics of data of geochemical sampling sites. It is statistics of

#### **Figure 6.**

*Geochemical spectrum of typical deposits in Manzhouli region after histogram stretching.*

**Figure 7.**

*Rasterized grayscale map of Na2O element content in the middle segment of Daxinganling metallogenic belt.*

all the pixels within the image. Basic statistics of a geochemical image involves the mean value, median, mode, range, contrast, etc.

Histogram is one of the important statistics of a geochemical image. Histogram refers to a discrete graph of probability density function of all gray values in the image, or it may be seen as a graphic expression of basic statistics of gray image. **Figure 9** is based on histogram and the chiefly related statistics. Under ENVI software, the calculation results of cumulative frequency can be obtained, and classification based on histogram analysis will be introduced in the next step.

Density slices to a gray geochemical image can create element anomalies. Cumulative frequency percentage can be used to determine anomalies or anomalies grading (**Figure 10**).
