Abstract:
Imaging sun in different wavelengths is invaluable for understanding its dynamic aspects and relevent impacts on space weather. The atmosphere of the Sun presents a number of puzzling physical phenomena of great importance. Processing of reconstructed solar images ensures meaningful visualization and provide additional informations. Imaging in particular wavelength band demands efficient imaging telescope with optimized parameters whereas appreciation of image requires study of features in different scales and their enhancement without introducing undesired artifacts. A proposal was submitted for a Solar Ultraviolet Imaging Telescope (SUIT) to ISRO to study the Sun in Near Ultraviolet Wavelengths (NUV, 200 – 400 nm). SUIT provides a new opportunity for imaging the Sun in NUV with apprecible image quality. This study addressed optimization of SUIT optics using suitable merit function and variables. It also includes simulation of image quality degradation due to geometry and alignment errors in optical surfaces. Appropriate compensator and its movement was found out for nullifying different errors in imaging optics both theoretically and through simulation revealing error bounds of individual parameters based on limit of merit function and restriction in compensator movements. Furthermore, Monte Carlo simulation has been performed to find worst fabrication and alignment error combination to confirm whether image degradation is acceptable. Thermal variation in space being an important factor to affect the image quality, temperature tolerance of the telescope system has also been explored. In the second part of this study multi-scale method such as wavelet has been used for visualization of fine structures in solar corona. Furthermore, active region and filament segmentation has been considered for solar full disc images enabling feature extraction of those regions namely area, centroid and slope which may be useful in studying time evolution of relevant solar features. Hence this study performs error budgeting of crucial parameters in solar NUV imaging telescope and illustrates relevant image processing techniques which can be embedded in the data pipeline.
