I have presented a method to determine the quality of granulation images that associates uniquely with every image a quality class. The discrete character of quality classes and the fact that very different images (e.g. those acquired after a long time interval) can be compared with them, make this method useful for characterizing the performance of instruments such as Themis IPM. The main advantages of the OWM are that it is easy to implement, it needs little computing and it also gives reliable results for small images, so that we can distinguish zones of different quality within the same image. This last characteristic makes it useful for a preliminary study when we want to use segmentation or restoration programs. In the first case, the quality map determines the zones of the image where it is more probable to find structures of small dimensions. In the second, it would allow us to restore in a different manner the zones more or less degraded. In both cases it would save computing time, thereby improving the results.
I wish to stress that image quality, as defined here, does not
directly represent the spatial resolution, although it is clear that better
quality also means higher resolution. In a forthcoming study, the precise
relationship between the two quantities will be clarified. One possible
development will be to distinguish within the same image regions with
different resolutions in order to correct the image locally.
|Figure 7: Analysis of the images obtained at Themis IPM during one hour of observation. Note how images of different quality classes can have the same contrast|
This work is based on observations obtained with the IPM mounted at the THEMIS-CNRS/INSU-CNR telescope at the Spanish Observatorio del Teide (Tenerife) of the Instituto de Astrofísica de Canarias. I thank also C. Briand, F. Berrilli, J.A. Bonet, B. Caccin, G. Ceppatelli, M. Collados, R. Corradi, G. Molodij and T. Roudier for their encouragement and useful suggestions. I thank T. Mahoney for the english supervision.
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