CN104615990A - Method for automatically recognizing macula based on Huairou full-disk single-color image - Google Patents

Abstract

The invention relates to a method for automatically recognizing macula based on a Huairou full-disk single-color image, and aims at solving the problems of extremely low efficiency caused by manually recognizing the profile of macula on disk and that mass data cannot be met in the solar physics in the domestic astronomy field. The method comprises the steps of extracting gradient information of the disk by the morphology bot-hat transformation according to the full-disk single-color image of the Huairou solar observing station of National Astronomical Observatories of China; removing the influence of inherent limb darkening rule of the disk by the fragmentation threshold method, so as to automatically recognize macula. Compared with other algorithms for recognizing the macula based on high-quality solar space data, the method has the characteristic that the macula of the ground images with relatively low quality and suffering from the interference of instrument noise can be precisely recognized. The method is applicable to automatic recognition of macula in the single-color images or white light images at other wave bands and can provide directly service to the fields of generator theory, solar action predication and space environment monitoring.

Description

A kind of sunspot automatic identifying method based on full-time the filtergram in Huairou

Technical field

The invention belongs to the image processing techniques in Solar Physics field, particularly a kind of automatic identifying method being applicable to sunspot in sun image.

Background technology

Sunspot is sun feature the most eye-catching on day face, is the most important index characterizing solar activity level.Analyze sunspot to studying the long-term mechanics of the sun, forecasting the harm that the power of solar flare and monitoring solar activity bring the mankind, all play very important effect.The attribute studying sunspot accurately must identify it.Early stage people are identified by naked eyes.But, in recent years along with observing capacity constantly promotes, new large-scale sun observation equipment constantly comes into operation, a large amount of sunspot observation data is had every day to produce, based on manual type because work efficiency is very low, and accuracy cannot ensure, cannot the demand of satisfying magnanimity data, utilize Computer Automatic Recognition sunspot to become active demand and trend.

Sun observation base, Huairou (HSOS) is one of important base of State Astronomical Observatory, CAS's astronomical sight and research, full-time Vector Magnetic Field telescope of base equipment 10cm bore, full-time the filtergram recording sunspot can be obtained every day, carry out the automatic identification of sunspot based on these images, can be relevant investigation and application and service is provided.

Automatically being identified in of sunspot is domesticly still belonged to blank, proposes certain methods abroad, such as: Zharkov et al. (2005) etc. utilizes frontier probe method and threshold method to extract the profile of sunspot; Curto et al. (2008) utilizes top cap conversion to extract the candidate region of sunspot, then screens these regions in conjunction with the parameter restriction of iteration; Suruchi et al. (2014) then make use of the method for level set to identify sunspot.On the whole, these methods mainly through extracting the gradient of sunspot, then carry out a definite limitation to identify sunspot to gradient.

Above all methods are all carry out sunspot identification based on the spatial data that quality is higher.But full-time photosphere filtergram of Huairou belongs to ground data, is subject to atmospheric interference, limited resolution during observation; The more important thing is, partial data is subject to noise of instrument interference, there is larger noise of instrument, and the position of noise of instrument in different pieces of information is not fixed near center, day face, and existing algorithm does not process for these problems.The present invention is directed to full-time the filtergram of China, propose a kind of new sunspot automatic identifying method, the interference of noise of instrument can be eliminated, improve the precision of sunspot identification in ground data, improve the utilization rate of China's sun observation data, for further investigation solar cycle, sun forecast and space weather monitoring provide convenient.

Leading reference annex

Summary of the invention

The object of the invention is for the some shortcomings existed in the filtergram image of full-time of Huairou (compared to external spatial data, resolution is lower, and be subject to the interference of noise of instrument), a kind of sunspot automatic identifying method proposed, has filled up domestic technological gap in this respect.

For achieving the above object, the present invention takes following design proposal:

(1) first, the heterogeneity of day face existence itself and the interference of cloud layer, the way based on global threshold is made to carry out sunspot identification infeasible, in order to overcome this problem, we have employed the morphology bot-hat transformation that can extract dark object under bright background, and (formula is as (1), (2), (3), (4), A represents original image, B and g representative structure element), remove a day face background, extract the gradient information on day face;

Dilation operation: $A\⊕B=\left\{z\right|{\left(\hat{B}\right)}_z\∩A\≠\mathrm{\Φ}\}---\left(1\right)$

Erosion operation:

Closed operation:

Bot-hat transformation: h=A-(A.g) (4)

(2) secondly, owing to being subject to the impact of the intrinsic limb darkening rule of the sun, the gradient information extracted exists near Mian center large, the problem that solar limb is little, to this, we adopt fragmentation threshold to process: utilizing higher thresholds near Mian center, adopt comparatively Low threshold to split respectively at solar limb place, obtain the candidate region of sunspot; Meanwhile, although noise of instrument is near Mian center, its Grad is lower relative to sunspot gradient, therefore, adopts higher thresholds to split, also substantially can eliminate noise of instrument in center, day face.Threshold value H chooses formula as (5), and (x, y) represents the coordinate of each pixel, and R represents day radius surface;

$H(x,y)=\left\{\begin{array}{cc}H1,& x^2+y^2<=(0.8*R)^2,\\ H2,& (0.8*R)^2<x^2+y^2<=R^2\end{array}\right.---\left(5\right)$

(3) last, because the center gray-scale value in each sunspot region is high, edge gray-scale value is low, and the difference limiting the gray scale of maximum, the minimum pixel of each candidate region at this must be greater than 5 pixels, and remove the candidate region not meeting this condition, finally obtain the sunspot on day face.

In sum, the present invention's advantage compared with existing several method is:

1. process of the present invention is picture quality lower ground face observation data, and the present invention is sensitiveer for the extraction at sunspot edge.

2. the present invention easily causes the noise of instrument of interference to eliminate to sunspot identification by day face, and this is that other technologies are not considered.

3. the sunspot that the present invention also can be used for other solar space data identifies automatically.

Accompanying drawing explanation

Fig. 1 is full-time filtergram original graph.

Fig. 2 carries out the result after closed operation process to original graph.

Fig. 3 is the gradient information on day face.

Fig. 4 is the binary map after adopting fragmentation threshold.

Fig. 5 is the recognition result of sunspot

Embodiment

Embodiments of the invention accompanying drawings is as follows:

The concrete implementation step of sunspot automatic identifying method of the present invention is as follows:

First, to raw data (see Fig. 1), closed operation is utilized to process, obtain a clean day face (see Fig. 2), the structural element be wherein set using to be radius be 15 circle, this, radius of hairy nevus was slightly larger radius ratio day, can eliminate black moles all on day face.

The second, Fig. 2 and Fig. 1 is subtracted each other, obtains the gradient information (see Fig. 3) on day face;

3rd, other method is utilized to extract the profile (developing relative program) of solar limb, calculate the radius in day face, and then the sun face in Fig. 3 is divided into two regions: the region in day 0.8, face radius is set to I1, the region of a day face 0.8-1 solar radius is set to I2.Threshold value H1 is adopted respectively to I1 and I2, H2 splits Fig. 3, obtain binary map 4.According to statistics, we choose H1=22 and H2=10.

4th, extract each region on Fig. 4, the difference meeting pixel maxima and minima is greater than to the region of 5 pixels, thinks sunspot, and with red-label, the region not meeting this condition is then abandoned.The sunspot of extraction is superimposed in Fig. 1 by we, obtains Fig. 5, and the red area in this figure represents the sunspot of identification of the present invention.

The various embodiments described above can in addition some changes under not departing from the scope of the present invention, therefore above explanation comprises and should be considered as exemplary, and is not used to the protection domain limiting the present patent application patent.

Claims (4)

1. the sunspot automatic identifying method based on full-time the filtergram in Huairou, it is characterized in that: compare other algorithms based on high-quality solar space data identification sunspot, the present invention is directed to quality lower and by noise of instrument interference ground image, higher to the accuracy of identification of sunspot.The step of the method is as follows:

(1) first, the heterogeneity of day face itself existence and be subject to the interference of cloud layer, the way based on global threshold is made to carry out sunspot identification infeasible, in order to overcome this problem, we have employed the morphology bot-hat transformation that can extract dark object under bright background, and (formula is as (1), (2), (3), (4), A represents original image, B and g representative structure element), remove a day face background, extract the gradient information on day face;

(2) secondly, owing to being subject to the impact of the intrinsic limb darkening rule of the sun, the gradient information extracted exists near Mian center large, the problem that solar limb is little, to this, we adopt fragmentation threshold to process: utilizing higher thresholds near Mian center, adopt comparatively Low threshold to split respectively at solar limb place, obtain the candidate region of sunspot; Meanwhile, although noise of instrument is near Mian center, its Grad is lower relative to sunspot gradient, therefore, adopts higher thresholds to split, also substantially can eliminate noise of instrument in center, day face;

(3) last, because the center gray-scale value in each sunspot region is high, edge gray-scale value is low, and the difference limiting the gray scale of maximum, the minimum pixel of each candidate region at this must be greater than 5 pixels, and remove the candidate region not meeting this condition, finally obtain the sunspot on day face.

2. a kind of sunspot automatic identifying method based on full-time the filtergram in Huairou according to claim 1, it is characterized in that: step 1) in, propose to utilize morphology bot-hat transformation to extract the gradient information in day face, morphologic formula is as shown in (1), (2), (3), (4).

Dilation operation: $A\&CirclePlus;B=\left\{z\right|{\left(\hat{B}\right)}_z\&cap;A\&NotEqual;\mathrm{\&Phi;}\}---\left(1\right)$

Erosion operation:

Closed operation:

Bot-hat transformation: h=A-(A.g) (4)

3. a kind of sunspot automatic identifying method based on full-time the filtergram in Huairou according to claim 1, it is characterized in that: step 2) in, for the interference of the intrinsic limb darkening rule in day face, and day face noise of instrument place to go, propose to utilize the method for fragmentation threshold to split, threshold value H chooses formula as (5).

$H(x,y)=\left\{\begin{array}{c}H1,x^2+y^2<=(0.8*R)^2,\\ H2,(0.8*R)^2<x^2+y^2<=R^2\end{array}\right.---\left(5\right)$

4. a kind of sunspot automatic identifying method based on full-time the filtergram in Huairou according to claim 1, it is characterized in that: step 3) in, to each sunspot region, the difference defining the gray scale of maximum, the minimum pixel in region must be greater than 5 pixels.