Abstract
In modern mineral exploration applications, remote sensing technologies have been widely used and affirmed by engineering and mineral industries due to their unique technical advantages. With the advancement of remote sensing technologies, multiple geological remote sensing-derived prospecting methods have been developed. With the development of more accurate sensors, the detection band has not been segmented, and the spectral resolution of such sensors is constantly being improved. Thus, the accuracy of remote sensing geological prospecting methods has improved, and geological prospecting results have shifted from being qualitative to quantitative in nature. In this article, high-resolution remote sensing images are used to extract the ore controlling factors of deposits. The color, shape, texture and other image shapes produced by high-resolution remote sensing images are fully exploited to comprehensively mine the available data utilizing mathematics, image processing methods and other technologies to systematically identify prospective target areas. Based on an analysis of the metalloorganic geological characteristics detected in the study area, combined with multisource data such as geophysical and geochemical exploration-derived observations, the proposed remote sensing model describing the deposits in the study area is summarized. The research results show that deposit location identification technologies based on high-resolution remote sensing image feature decomposition have the potential to provide a reliable basis for peripheral exploration and deposit positioning in geological and mineral exploration studies.
Highlights
Remote sensing technology is a necessary means of geological exploration
Intersection positions are considered prospective remote sensing target areas. These results are this study are as follows: make full use of the color, shape, texture and other image shapes provided by high-resolution remote sensing data; fully mine the available data using mathematics, image processing, and other technologies; comprehensively identify prospecting target areas; and provide a reliable basis for the peripheral exploration and deposit positioning of mining areas
The color, shape, texture and other image shapes produced by high-resolution remotely sensed data are fully utilized to fully mine the data through mathematics, image processing methods and other technologies to comprehensively determine potential prospect target areas
Summary
Remote sensing technology is a necessary means of geological exploration. Traditional remote sensing prospecting methods are generally based on low to medium spatial resolution, multispectral or hyperspectral image data. The second is to extract geological structures and alteration details from multispectral remote sensing images to comprehensively analyze the regional metalloorganic geological conditions and determine the prospecting target area [2] Pixel-based remote sensing image analysis methods cannot meet the requirements of high-resolution remote sensing image information extraction and have become the bottleneck of large-scale remote sensing applications [6]. Intersection positions are considered prospective remote sensing target areas These results are this study are as follows: make full use of the color, shape, texture and other image shapes provided by high-resolution remote sensing data; fully mine the available data using mathematics, image processing, and other technologies; comprehensively identify prospecting target areas; and provide a reliable basis for the peripheral exploration and deposit positioning of mining areas. We incorporate formula (6) and use the image pixel reconstruction formula to reconstruct the time and frequency
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