Aurora image sequence classification method based on space-time polarity local binary pattern

A local binary mode and image sequence technology, which is applied in the field of image processing, can solve the problems of increasing classification time and high vector dimension, and achieve the effects of improving classification accuracy, low computational complexity, and improving processing speed

Inactive Publication Date: 2014-08-06
XIDIAN UNIV
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However, the feature vector dimension obtained by using Volume LocalBinary Patterns

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  • Aurora image sequence classification method based on space-time polarity local binary pattern
  • Aurora image sequence classification method based on space-time polarity local binary pattern
  • Aurora image sequence classification method based on space-time polarity local binary pattern

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[0021] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0022] Step 1. Preprocess the input aurora image sequence by rotating it counterclockwise by 62.63° to obtain the preprocessed aurora image sequence.

[0023] Since there is a 62.63° deviation between the north-south direction in the aurora image and the actual geomagnetic north-south direction, it is necessary to preprocess the input aurora image sequence by 62.63° counterclockwise, that is, to align the north-south direction in the aurora image with the actual geomagnetic north-south direction.

[0024] Step 2, divide the preprocessed aurora image sequence into blocks with different number of blocks M times.

[0025] (2a) The first block, that is, the preprocessed aurora image sequence is divided into 1×1 three-dimensional vertical blocks, which are actually the original preprocessed aurora image, denoted as B 1 1 ;

[0026] (2b) The second block, that is, the preproce...

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Abstract

The invention discloses an aurora image sequence classification method based on a space-time polarity local binary pattern. The aurora image sequence classification method based on the space-time polarity local binary pattern mainly resolves the problem in the prior art that the classification efficiency is not high. The aurora image sequence classification method comprises the steps that (1) preprocessing of rotating an aurora image sequence counterclockwise by 62.63 degrees is carried out; (2) the preprocessed aurora image sequence is chunked multiple times, and the numbers of chunks of the multiple times are different; (3) a polarity local binary pattern PVLBP algorithm is used, the polarity local binary pattern characteristic PVLBP of each chunk is extracted, and the PVLBP characteristics of all the chunks are sequentially connected to obtain a space-time polarity local binary pattern characteristic ST-PVLBP; (4) the space-time polarity local binary pattern characteristic ST-PVLBP of the aurora sequence is input into a support vector machine (SVM) classifier to obtain a classification result. The aurora image sequence classification method based on the space-time polarity local binary pattern keeps high classification accuracy, shortens the classification time, improves classification efficiency, and can be applied to scene classification and event detection.

Description

technical field [0001] The invention belongs to the technical field of image processing, and specifically relates to a method for classifying aurora image sequences, which can be used for scene classification and event detection. Background technique [0002] The aurora is a beautiful brilliance formed by the interaction of the solar wind, the interplanetary magnetic field, and the Earth's magnetosphere. It is the most intuitive trace of the ionosphere in the energy coupling between the sun and the earth and various magnetosphere dynamics. The dayside aurora reflects the various dynamic processes of solar wind-magnetosphere-ionosphere coupling on the dayside. Through long-term observation of the dayside aurora and in-depth research on its shape, intensity, movement and other characteristic changes, the space weather process The study of transformation law is of great significance. [0003] Existing researchers have studied the aurora, mainly using various means to conduct j...

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Application Information

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IPC IPC(8): G06K9/62G06K9/66
Inventor 韩冰廖谦高新波仇文亮邓成王秀美王颖
Owner XIDIAN UNIV
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