| Aurora is the most effective and direct reflection of geomagnetic activity and it ischanging and moving constantly.The form of aurora is varied under the influence of thesolar wind. The research of aurora has the important meaning for the research of thegeomagnetic activity, and the most effective way of which is to study the aurora image.The aurora images shoot by our country’s polar stations needs to be transmitted to theresearchers in the country due to the relationship of the geographical location, so theimage compression technology is needed in this procession. The mainly research resultsof this paper are as follows:1. According to the relationship between geomagnetic activity and the sun’s activity,we have found out the factor K_p, which can describe the magnetic activity mosttypically, from multiple description factors of geomagnetic activities. And then,combined with the KEO figure of aurora image, the positive correlation betweenthe aurora form and strength changes and the K_pindex has been found out.2. Several2d image compression method have been studied, and the four types ofaurora image: arc shape, mian shape, screen, and the rays of the image of singlesaurora respectively have been tested several traditional compression algorithm,such as Huffman code, the run-length coding, arithmetic coding, etc. According tothe development of the recent research of wavelet, the performances of three kindsof typical image compression algorithm used for aurora image compression havebeen analyzed under experiments.3. Those2d image compression methods have low compression efficienty, andindividual method of them is loss, but the requirement of aurora imagecompression is lossless, so this paper according to the correlation between theframes of3d aurora image, the3d image compression algorithm based on thecontext of prediction has been improved and programmed. And a betterperformance algorithm has been achieved, which can appliesd to3d aurora imagecompression algorithm effectively. |
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