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Automated detection of filaments on full disk H  images

Automated detection of filaments on full disk H  images. EGSO WP5. Nicolas Fuller and Jean Aboudarham Meudon Observatory / LESIA October 2003. Automated Detection of Filaments / NF & JA 2003. Automated Detection of Filaments / NF & JA 2003. Cleaning Process. Darkening. Dust lines.

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Automated detection of filaments on full disk H  images

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  1. Automateddetectionof filaments on full disk H images EGSO WP5 Nicolas Fuller and Jean Aboudarham Meudon Observatory / LESIA October 2003

  2. Automated Detection of Filaments / NF & JA 2003

  3. Automated Detection of Filaments / NF & JA 2003 Cleaning Process Darkening Dust lines

  4. Automated Detection of Filaments / NF & JA 2003 Cleaning process / Intensity normalization 1 • Need to compute the slow variations of the background • Use of a large median filter on a resized image • The first approximation is influenced by large bright plages and large filaments • Resize the image I to a smaller scale -> Is • Apply a median filter with a large window to Is • Resize to original scale (->B) and subtract from I -> I’ • From I’define 2 thresholds to roughly locate filaments and bright plages • Replace their value with the corresponding values in B -> I” • Apply step 1 to 3 to I” and get the final background and the normalize image

  5. Automated Detection of Filaments / NF & JA 2003 Cleaning process / Intensity normalization 2 - = - =

  6. Automated Detection of Filaments / NF & JA 2003 Cleaning process / Dust lines removal 1 • Need to compute a binary image with most of the • line points set to 1 and the background to 0 : • Threshold • Thinning morphological operator

  7. Original Threshold Thinning Hough transform Threshold Hough backprojection Line pixels locations Pixels values correction Automated Detection of Filaments / NF & JA 2003 Cleaning process / Dust lines removal 2

  8. Before and after enhancement Automated Detection of Filaments / NF & JA 2003 Image enhancement • To enhance the image sharpness we use a Laplacian filter • Filaments contours are better defined • Allows to detect the thinnest parts of the filaments more efficiently g(x,y) = f(x,y) –2f(x,y) where2f = 2f/x2 + 2f/y2 Digital implementation:

  9. Automated Detection of Filaments / NF & JA 2003 Region Growing Definition: “procedure that groups pixels into larger regions based on predefined criteria. It starts with a set of ‘seed’ points and from these grow regions by appending to each seed those neighboring pixels that have properties similar to the seed”

  10. Automated Detection of Filaments / NF & JA 2003 Region Growing / Seeds detection To find the seed points we apply a windowed threshold: The pixels statistics in each window (200*200) are computed and the threshold is given by: Twin = Mwin –  x win M : Mean  : constant  : standard deviation

  11. Automated Detection of Filaments / NF & JA 2003 Region Growing For each seed we define an intensity range which is a criteria to append connected pixels to the seed: [ 0, Tbr ] where Tbr = Mbr –  x br ( brstands for Bounding Rectangle ) A minimum region size is also defined

  12. Automated Detection of Filaments / NF & JA 2003 Region growing / BBSO The process has been tested on other Ha full disk observations :  Big Bear Solar Observatory example

  13. Morphological closing Skeleton  Length/centre/Chain Code… Morphological thinning / pruning Automated Detection of Filaments / NF & JA 2003 Shape analysis / Morphological operators Chain code direction numbers

  14. Automated Detection of Filaments / NF & JA 2003 Parameters : examples GRAV_C_CAR_LAT DOUBLE -18.297280 GRAV_C_CAR_LON DOUBLE 337.64961 BRPIX_X_LL DOUBLE 562.00000 BRPIX_Y_LL DOUBLE 418.00000 BRPIX_X_UR DOUBLE 574.00000 BRPIX_Y_UR DOUBLE 430.00000 SAMPLECOUNT LONG 58 AREA DOUBLE 2.8334533 SKE_LEN_DEG DOUBLE 2.254509 ELONG DOUBLE 0.90625000 MEAN_INT_RATIO DOUBLE 0.83272228 FEAT_MAX_INT DOUBLE 978.00000 FEAT_MIN_INT DOUBLE 689.00000 FEAT_MEAN_INT DOUBLE 869.36206 ENC_MET STRING 'CHAINCODE' COD_PIX_X DOUBLE 572.00000 COD_PIX_Y DOUBLE 417.00000 COD_SKE_PIX_X DOUBLE 574.00000 COD_SKE_PIX_Y DOUBLE 418.00000 SKE_CHAIN STRING '33332233334343' BND_CHAIN STRING '00123322222234433443444566707777677076'

  15. Automated Detection of Filaments / NF & JA 2003

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