A method for identifying solar rice grains in astronomical images

Abstract

The invention relates to a method for identifying a solar granule in an astronomic image, and belongs to the fields of astronomy technology and image processing. The method comprises the steps of: firstly, receiving a solar photospheric image I1, using band-pass filtering to carry out de-noising, and obtaining a de-noised image I2; then according to intensity distribution of the image I2, judging whether sunspots exist in the image; carrying out top-hat transformation and bottom-hat transformation respectively on the image I2, and obtaining a top-hat transformation image and a bottom-hat transformation image; then adding the top-hat transformation image to the solar photospheric image, obtaining an image I3, and carrying out subtraction between the image I3 and the bottom-hat transformation image to obtain an image I4; respectively subjecting the image I4 respectively to open operation of a phase congruency method, binaryzation and morphology and hole filling operation, and obtaining an image I7; and carrying out watershed transformation operation on the image I7, and obtaining a binary image of a granule cellular boundary. By adopting the method for identifying the solar granule in the astronomic image, the granule organization high in contrast and clear in edge can be well identified, and the granule characteristics low in contrast and fuzzy in edge can also be well identified.

Description

technical field

[0001] The invention relates to a method for identifying solar rice grains in astronomical images, belonging to the fields of astronomical technology and image processing. Background technique

[0002] With the development of science and technology, people realize that solar activities are of great significance to the life of the earth and human beings. The study of solar activity is an important aspect of astronomy, and the study of solar granules has attracted more and more attention from researchers.

[0003] Currently, there are many traditional methods for identifying rice grains in astronomical images. These methods can be summarized into two categories: one is the gradient-based recognition method, and the other is the intensity-based recognition method. Due to the characteristics of rice grains covering a very large intensity range, uneven distribution, and blurred edges, the method of identifying rice grains based on gradients and intensity thresho...

Examples

Embodiment 1

[0038] Embodiment 1: as Figure 1-21 As shown, a method for identifying solar rice grains in astronomical images first receives the solar photosphere image I to be identified 1 , use bandpass filter to denoise, and get the denoised image I 2 ; Then according to the denoised image I 2 Judging whether there are sunspots in the image by the intensity distribution of the image; then the denoised image I 2 Perform top-hat transformation and bottom-hat transformation respectively to obtain the top-hat transformation image and bottom-hat transformation image; then add the top-hat transformation image and the solar photosphere image to obtain the image I 3 , the image I 3 Subtract from the bottom hat transformed image to get image I 4 ; for image I 4 Through the phase consistency method, binarization, morphological opening operation and hole filling operation in sequence, the characteristic structure image of rice grain shape I is obtained 7 ; For rice grain shape feature struct...

Embodiment 2

[0048] Embodiment 2: as Figure 1-21 As shown, a method for identifying solar rice grains in astronomical images first receives the solar photosphere image I to be identified 1 , use bandpass filter to denoise, and get the denoised image I 2 ; Then according to the denoised image I 2 Judging whether there are sunspots in the image by the intensity distribution of the image; then the denoised image I 2 Perform top-hat transformation and bottom-hat transformation respectively to obtain the top-hat transformation image and bottom-hat transformation image; then add the top-hat transformation image and the solar photosphere image to obtain the image I 3 , the image I 3 Subtract from the bottom hat transformed image to get image I 4 ; for image I 4 Through the phase consistency method, binarization, morphological opening operation and hole filling operation in sequence, the characteristic structure image of rice grain shape I is obtained 7 ; For rice grain shape feature struct...

Embodiment 3

[0049] Embodiment 3: as Figure 1-12 As shown, a method for identifying solar rice grains in astronomical images first receives the solar photosphere image I to be identified 1 , use bandpass filter to denoise, and get the denoised image I 2 ; Then according to the denoised image I 2 Judging whether there are sunspots in the image by the intensity distribution of the image; then the denoised image I 2 Perform top-hat transformation and bottom-hat transformation respectively to obtain the top-hat transformation image and bottom-hat transformation image; then add the top-hat transformation image and the solar photosphere image to obtain the image I 3 , the image I 3 Subtract from the bottom hat transformed image to get image I 4 ; for image I 4 Through the phase consistency method, binarization, morphological opening operation and hole filling operation in sequence, the characteristic structure image of rice grain shape I is obtained 7 ; For rice grain shape feature struct...

technical field

[0001] The invention relates to a method for identifying solar rice grains in astronomical images, belonging to the fields of astronomical technology and image processing. Background technique

[0002] With the development of science and technology, people realize that solar activities are of great significance to the life of the earth and human beings. The study of solar activity is an important aspect of astronomy, and the study of solar granules has attracted more and more attention from researchers.

[0003] Currently, there are many traditional methods for identifying rice grains in astronomical images. These methods can be summarized into two categories: one is the gradient-based recognition method, and the other is the intensity-based recognition method. Due to the characteristics of rice grains covering a very large intensity range, uneven distribution, and blurred edges, the method of identifying rice grains based on gradients and intensity thresho...

Examples

Embodiment 1

[0038] Embodiment 1: as Figure 1-21 As shown, a method for identifying solar rice grains in astronomical images first receives the solar photosphere image I to be identified 1 , use bandpass filter to denoise, and get the denoised image I 2 ; Then according to the denoised image I 2 Judging whether there are sunspots in the image by the intensity distribution of the image; then the denoised image I 2 Perform top-hat transformation and bottom-hat transformation respectively to obtain the top-hat transformation image and bottom-hat transformation image; then add the top-hat transformation image and the solar photosphere image to obtain the image I 3 , the image I 3 Subtract from the bottom hat transformed image to get image I 4 ; for image I 4 Through the phase consistency method, binarization, morphological opening operation and hole filling operation in sequence, the characteristic structure image of rice grain shape I is obtained 7 ; For rice grain shape feature struct...

Embodiment 2

[0048] Embodiment 2: as Figure 1-21 As shown, a method for identifying solar rice grains in astronomical images first receives the solar photosphere image I to be identified 1 , use bandpass filter to denoise, and get the denoised image I 2 ; Then according to the denoised image I 2 Judging whether there are sunspots in the image by the intensity distribution of the image; then the denoised image I 2 Perform top-hat transformation and bottom-hat transformation respectively to obtain the top-hat transformation image and bottom-hat transformation image; then add the top-hat transformation image and the solar photosphere image to obtain the image I 3 , the image I 3 Subtract from the bottom hat transformed image to get image I 4 ; for image I 4 Through the phase consistency method, binarization, morphological opening operation and hole filling operation in sequence, the characteristic structure image of rice grain shape I is obtained 7 ; For rice grain shape feature struct...

Embodiment 3

[0049] Embodiment 3: as Figure 1-12 As shown, a method for identifying solar rice grains in astronomical images first receives the solar photosphere image I to be identified 1 , use bandpass filter to denoise, and get the denoised image I 2 ; Then according to the denoised image I 2 Judging whether there are sunspots in the image by the intensity distribution of the image; then the denoised image I 2 Perform top-hat transformation and bottom-hat transformation respectively to obtain the top-hat transformation image and bottom-hat transformation image; then add the top-hat transformation image and the solar photosphere image to obtain the image I 3 , the image I 3 Subtract from the bottom hat transformed image to get image I 4 ; for image I 4 Through the phase consistency method, binarization, morphological opening operation and hole filling operation in sequence, the characteristic structure image of rice grain shape I is obtained 7 ; For rice grain shape feature struct...

Images