1. Faint coronal structures and the possibilities of visualization Marcel Bělík (1) Miloslav Druckmuller (2) Eva Marková (1) Ladislav Křivský (1) (1) Observatory Úpice, Czech Rep. (2) VUT Brno, Czech Rep.

2. What is the main goal? To get all possible information from the unique picture or the set of pictures !! What can we do ?? try to use the radial filter try our potentiality to redraw the details from the individual negatives try our potentiality in dark room try to compose several pictures by using „digital dark room“ try to use the adaptive numerical methods for solar eclipse pictures processing We can:

3. On the individual picture of the total solar eclipse we can see: But … we can see more and more:

4. Using of the radial filter grey filter with grade density (~ decrease of coronal brightness) located in focal plane in front of photographic plate The difficulties: long exposure times necessity of very accurate orientation of all axes in optical system difference between theoretical and practical decrease of coronal brightness Redraw the structures from the individual negatives In the case of very precise redraw - not so bad method It is relative accurate, but … very elaborated Newkirk, G., Jr.: 1967, Ann.Rev.Astron.Astrophys., 5, 231.

5. „Dark room“ processing Both used methods are very laborious and practically nonreprocessed composition of big number of short exposure pictures „dark room magic experiments“ Composition of several pictures in „digital dark room“

6. Composition of several pictures in „digital dark room“ This method use some picture operations like radial blur, unsharp masking, rotations, masking and so on to get as realistic as possible picture of all visible corona. The main problem of all these method is the creation of picture artefacts, which could be exchanged with real events. All these methods prefere radial or tangential directions on the picture moreover.

7. Numerical methods for solar eclipse pictures processing There exist several, let us say, classical solutions of the mentioned problem. The most powerful are nonlinear pixel value transformations based on image histogram analysis. The best known one is the so called histogram equalization. Another solution uses the two-dimensional discrete Fourier transform. While any phase spectra manipulation causes a significant image degradation, amplitude spectra modification is for human eye generally acceptable and it may increase the subjective quality of an image. It can be successfully used in visualization of images with high dynamic range. Even if these methods are useful in many branches of scientific imaging methods their abilities are very limited.

8. Adaptive numerical methods for solar eclipse pictures processing The human vision itself gives a lot of motivation for numerical image processing. The most important feature of human vision is adaptivity. An image is by human eye not observed as the whole. It is analyzed in small elements and the parameters as sensitivity, focussing, aperture etc. are changed in order to reach optimum local view. The human eye is from technical point of view a diferential analyser and it has only limited ability to measure absolute brightness. The comparation of brightness is done on a picture element neighbourhood which is of variable shape depending on the image content. Mathematical numerical methods which modify the algorithm according to local image properties as human eye does are called adaptive filters.

9. Adaptive numerical methods for solar eclipse pictures processing Adaptive filter for high dynamic range image processing must present several types of adaptivity: The first type of adaptivity is that of pixel value transformation function. The transformation function is usually derived from image histogram, so the adaptivity may be achieved by using the local histogram computed on some pixel neighbourhood instead of whole image histogram. So called adaptive histogram equalization is one of these methods based on this principle. The creation of suitable pixel neighbourhood for histogram computing is very important. Any of fixed type neighbourhood (for example square) cannot give good results because it does not respect boundaries between areas with significantly dierent histograms. Therefore it is necessary to construct a neighbourhood according to local properties of image i.e. to use adaptive neighbourhood. This is the second very important type of adaptivity. The third type of adaptivity is based on additive noise analysis. The pixel value transformation function must be corrected according to local parameters, usually according to standard deviation of additive noise. If the noise is independent on the image the standard deviation can be estimated by means of autocorrelation function analysis.

10. Adaptive numerical methods for solar eclipse pictures processing Angola 2001, Observatory Úpice

11. Adaptive numerical methods for solar eclipse pictures processing Venezuela 1998, Observatory ÚpiceHungary 1999, Miloslav Druckmuller

12. All images published in the part „Adaptive numerical methods for solar eclipse pictures processing“ were processed using the scientific image analyzer ACC (Adaptive Contrast Control) version 4.0 which is the product of Czech firm SOFO *. This PC software consists of a lot of procedures for exact image processing including the unique ACC algorithm for nonlinear local contrast transformation. * Miloslav Druckmuller is a member of the team developing the ACC image analyzer. Image analyzer ACC (Adaptive Contrast Control) Conclusion There is a lot of different methods to extract detail structures of eclipse white-light solar corona. Some of them product very interested results, but this is made to the prejudice of any other picture parameters (resolution, photometry, etc.) It seems adaptive numerical methods for solar eclipse pictures processing are the best method for detailed analyze of coronal structure (and probably not only for it). This paper was supported by the grant No. 205/01/0420 GAČR.