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Mastering Deconvolution in SIRIL: Advanced Image Sharpening Techniques
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In this SIRIL post-processing tutorial by Alexander Curry he will discuss using deconvolution, he will delve into the advanced topic of image sharpening. In Part 1, Alex introduces the concept of deconvolution, explaining its purpose in correcting and sharpening distorted star images caused by atmospheric and optical effects. He will demonstrate how to generate a Point Spread Function image (PSF) using SIRIL's tools to characterize the stars in an image, emphasizing the importance of adjusting parameters like radius, threshold, and roundness to refine star detection.
In Part 2, Alex focuses on the non-blind deconvolution process. He will explain the significance of various parameters such as the regularization parameter, stopping criterion, iterations, and algorithm selection. He will highlight the iterative nature of deconvolution, recommending adjustments to achieve optimal sharpness without introducing artifacts. Alex will conclude by emphasizing the importance of high frame counts and proper parameter tuning to achieve better deconvolution results, ultimately leading to sharper and more detailed images.
In Part 2, Alex focuses on the non-blind deconvolution process. He will explain the significance of various parameters such as the regularization parameter, stopping criterion, iterations, and algorithm selection. He will highlight the iterative nature of deconvolution, recommending adjustments to achieve optimal sharpness without introducing artifacts. Alex will conclude by emphasizing the importance of high frame counts and proper parameter tuning to achieve better deconvolution results, ultimately leading to sharper and more detailed images.
PART 1
SIRIL Deconvolution Part 1
11 minutes
PART 2
SIRIL Deconvolution Part 2
8 minutes
PART 1
SIRIL Deconvolution Part 1
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