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Poster Session 3
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Gold Mineralization Information Processing On TM Images
The General Ideal Of "Micro-Different Information Processing"
Many researchers become used to understanding and analyzing remote sensing images with the views of conventional geology. This results in having ignored the own physical characteristics and information mechanism of satellite-based images. Based on information theory, "Micro-difference information processing" looks into the geological information characteristics existed in TM data. Its general view are as follows:
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About geological remote sensing information.
As the description above, all the objects on the surface are information carriers because of the reason that remote sensing information is the result of all the objects on the surface interacting with electromagnetic wave. By substance transmission and percolation, geological bodies and structures under soil or vegetation coverage will cause some changes of the surface, such as physical characteristics and chemical component, water contains as well as ecological variation of plants. These changes may lead to a weak presentation in TM images, and they probably indicate geological anomalies related to gold mineral exploration. Therefore this kind of weak information is just the target that we usually operate on by image processing. In other word, the key issue of gold mineralization information extracting from TM images is to dispel the common disturbing information and achieve the weak variation information.
- About vegetation coverage.
Some remote sensing geologists look upon vegetation as only a coverage to geological bodies or geological anomalies, and they emphasize to apply satellite-data acquired in winter to reduce the influence of vegetation. Meanwhile they advise to get rid of vegetation coverage in image processing. Nevertheless high content (or loss) of some chemical elements in soil may lead to ecological variation as well as change of plants' spectral characteristics. So, in the areas of heavy vegetation coverage, we should pay more attention to bio-geochemical effect on TM images and select the TM temporal data for distinguished or the growing appearance of vegetation is most different, namely bio-geochemical effect is most obvious.
- About application preprocessing of remote sensing geology.
Similar to information recognition in signal processing, the signal (information), as well mean in TM data, is relative to "noise," and it will change with the application purpose. Some part of the data is signal in one application, to another applications, it is probably only but noise (non-contribution information). For the information (such as alteration information) we need normally appears very weak, and the common information, like heavy noise disturbing in signal processing, is what we unexpected in TM images. Therefore, it is very significant to perform image preprocessing in geological application of remote sensing. Its function can be regarded as that of restraining noise and improving "signal to noise ratio" (S/N) in signal processing model.
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