Research On The Method Of Identifying The Structure Of The Solar Coronal Loop Based On Guided Filtering And Wavelet Transform

The corona is the outer layer of the solar asmosphere.The bright loop-like structures in the corona,which are called coronal loops,are hot plasma to be bound to the solar coronal magnetic fields.Studying these magnetic features can help to better understand the dynamics of coronal magnetic fields and coronal oscillations,and further clearify the debate of coronal heating.Accurate identifying coronal loops are crucial for the relevant studies.Therefore,it is particularly urgent to find a method to identify and extract coronal loops accurately.However,through our analysis of the causes of coronal loop structure and its environment,we find that the formation of coronal loops is influenced by the solar coronal magnetic field,which is quite complex,so that the edges of the coronal loops are blurred,the adjacent coronal loops are difficult to distinguish,and the interference of flares,spongy bright spots,etc.It is very difficult to identify and extract the loop-like structures.In this case,we propose a novel algorithm based on guided filtering and wavelet transform modulus maxima to automatically detect and extract them.The images observed by the Transition and Coronal Explorer(TRACE)intruments in the 171 ? channel are selected to illustrate the porcess and further evaluate the performance of the algorithm.The steps are as follows: we use(1)Normalization of image;(2)a fuzzy function to enhance the contrast of solar corona images;(3)guided filtering to highlight the edges of coronal loops;(4)wavelet transform modulus maxima to detect coronal loops;(5)image binarization to extract coronal loops;(6)morphological operate to remove those non-loop structures and keep the coronal loop structure in the image as much as possible.(7)Further removing the non-coronal loop structure by using the variance of the abscissa and the ordinate of each connected object of the pixel marked as an coronal loop structure in the image and get the final recognition result of coronal loops.In order to verify the validity,accuracy and completeness of the proposed method,we use the coronal loop structure identified by the method to compare with the recognition results in the existing literature.In order to verify the applicability of this method,we use the method presented in this paper to identify and extract the coronal loops in the coronal images observed by the Transition and Coronal Explorer(TRACE)and the Atmospheric Imaging Assembly on the Solar Dynamics Observatory(SDO/AIA)intruments in the 171 ? channel.Finally,we discussed the influence of threshold and parameters used in this method on the recognition results.The results demonstrate that the proposed algorithm has significant advantages over provious identification methods and the detected and extracted structures can be further applied to scientific researchs.