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Salvaging Images with Pixel Math: Warren Keller's Emergency Flats Technique
In this tutorial, Telescope Live tutor and Masters of Pixinsight presents a creative solution for recovering astrophotography images lacking flat field calibration. When faced with dust motes and other issues, Warren demonstrates using Pixel Math in PixInsight to apply a different master flat to a master light after initial calibration. Through a specific Pixel Math expression, he shows how to reduce star artefacts and correct gradients, turning an unusable image into a viable one. Warren’s method provides a practical tip for handling emergencies in astrophotography processing.
Mastering Gradient Correction in PixInsight With Warren Keller: Tools and Techniques
Join award winning astrophotographer and author of Inside Pixinsight, Warren Keller, as he dives deep into gradient correction.
This webinar will address the 4 most common plugins and softwares for dealing with gradient correction in your astro images, and more importantly how best to utilize them.
Warren will cover the following plugins: Gradient Correction, GradientXTerminator and Dynamic Background Extraction highlighting the benefits and limitations of each plugin and when they should be used.
Effortless LRGB Combination in APP: Transforming the M83 Galaxy
In this comprehensive tutorial, Telescope Live tutor Ryan Voykin walks you through a streamlined and effective method for combining LRGB channels using Astro Pixel Processor (APP). Ryan demonstrates the unique channel combination process in APP, which allows for the integration of up to nine different channels, including HA LRGB and SHO combinations. He highlights APP’s efficiency, from faster stacking compared to PixInsight to versatile auto-stretch options. This tutorial also covers step-by-step instructions for loading data, generating master files, and utilizing APP’s various tools to clean up and enhance your images. With practical tips and a user-friendly workflow, Ryan shows how APP can simplify and significantly improve your astrophotography processing.
Mastering Deconvolution in SIRIL: Advanced Image Sharpening Techniques
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.