Auroral oval segmenting method based on brightness self-adaptive level set

Abstract

The invention discloses an auroral oval segmenting method based on a brightness self-adaptive level set, which mainly solves the defects of the existing auroral oval segmenting method that the segmentation precision is low, the robustness is poor and the application range is small. The auroral oval segmenting method comprises the following steps of (1) adopting a morphology component analysis method to preprocess an ultraviolet aurora image; (2) establishing a morphology saliency map to be used as shape characteristics of the auroral oval; (3) utilizing the marginal curve of the morphology saliency map to initialize a level set function; (4) calculating the brightness self-adaptive level set evolution speed and a stop function; (5) updating the level set function according to the brightness self-adaptive level set evolution equation; and (6) extracting a zero level set curve after being updated and utilizing the zero level set curve as the auroral oval margin to be outputted. Due to adopting the auroral oval segmenting method, the phenomenon of the traditional segmenting method such as result deviation and margin leakage can be avoided, advantages such as high segmentation precision and strong robustness can be achieved, and the method is applicable to the segmentation of different ultraviolet auroral images.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to target segmentation of images captured in ultraviolet bands, which can be used to segment aurora egg regions from complex ultraviolet aurora images. Background technique [0002] Aurora is an important natural luminous phenomenon in space optical radiation in polar regions. It is excited by the interaction of solar wind and magnetotail charged particle bodies with molecules and atoms in the atmosphere in the near-Earth space. Its occurrence and development are closely related to the solar activity cycle and the intensity of geomagnetic activity. Ultraviolet band imaging detection can capture the extremely weak energy scattering that is difficult to observe in any other band, and then conduct all-weather and all-area detection of the energy fluctuation of the sun entering the polar region of the earth, thus becoming the main means of aurora detection. The aurora egg region...

AI Technical Summary

Problems solved by technology

However, the method of Li et al. initializes the curve randomly, and the difference between the background and the target gray level of the aurora image is small. If the initial curve is far away from the target edge, the segmentation result will deviate greatly.

At the same time, the curve evolution speed and stop function in this method have no correlation with the gray value around the curve, so when dealing with weak edge problems such as aurora egg segmentation, even if an initialization curve close to the target edge is selected, the Large edge leakage occurs

[0005] In summary, neither the existing aurora egg segmentation method nor the commonly used level set image segmentation method can achieve satisfactory segmentation results for ultraviolet aurora images.

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