![]() ![]() Simple subtraction is the best star extraction method to use with linear images, and will result in the best star color accuracy. If generating a star image from a linear image, don't select the Unscreen option, which is for nonlinear (stretched) images.Auto-stretch will destroy this STF information and give a false impression of the significance of very faint background residual pixel values. StarXTerminator will translate the STF parameters of the original image to the stars image to make subsequent stretching easier. If generating a star image, don't use STF Auto Stretch on the resulting stars image.Other processing operations such as masked stretch, high dynamic range processing, etc., may also alter star profiles enough that they will not be recognized as stars by the neural network. In particular, an arcsinh stretch and a generalized hyperbolic stretch (GHS) can create star profiles that are indistinguishable from small elliptical galaxies, and will result in StarXTerminator not removing, or only partially removing, the stars. Any processing that significantly alters star profiles relative to this method may reduce the effectiveness and/or quality of star removal. The MTF stretch is the same method used by PixInsight's HistogramTransformation tool.When processing linear images, StarXTerminator internally performs such a stretch automatically, then precisely reverses it after processing to return the image to a linear state. StarXTerminator is trained on images stretched using a simple midtones transfer function (MTF). ![]() This will generally produce the best results, and gives the added flexibility of being able to stretch the starless and stars images separately depending on the desired end result. ![]() Use StarXTerminator as early in the processing flow as possible, ideally right after integration, with the data still in a linear state (i.e., prior to any stretching).Here are some usage notes and tips for the PixInsight and Photoshop versions of StarXTerminator: PixInsight We continually train the neural network on new data, and RC Astro is always happy to receive suggestions for improvement. Perhaps your instrument setup is unique and your data can be included in the training of the next version of the neural network. If still getting poor results, feel free to contact support. If despite these efforts you find a case where StarXTerminator does not seem to perform well, review the usage notes below. Invest the time needed to get your optical setup functioning well, not only for better star removal, but also for the best detail and contrast in nebulas and galaxies achievable with your equipment. It may not function well on images taken with instruments with serious optical deficiencies. StarXTerminator was also trained to handle a limited range of optical aberrations such as minor focus errors, guiding errors, coma, field curvature, etc. It will produce excellent results on a majority of images, but occasionally there may be cases where stars are not completely removed, or some minor non-stellar structure is. StarXTerminator was trained to work on images produced with a very wide range of instruments, from camera lenses to the James Webb Space telescope. ![]() Keep in mind that star removal is an extremely challenging problem, and no star removal tool will ever perform 100% perfectly on all images. This limitation is per-computer, so using StarXTerminator in Photoshop and PixInsight on the same computer, for example, only consumes one license activation. Permanent licenses can be used on two computers – up to three upon request – provided you are the primary user of StarXTerminator on all of them. StarXTerminator has a "universal" licensing system: a permanent license for any version (Windows/Mac/Linux, Photoshop/PixInsight) will work for any other version. The end result is a very smooth elimination of stars, with minimal residual artifacts. Small stars, big stars, huge stars, and even diffraction spikes are recognized and removed, with minimal impact to non-stellar features. This network has been extensively trained on photographs from a wide range of instruments, from camera lenses to the James Webb space telescope. StarXTerminator uses an advanced convolutional neural network with a unique architecture suited to this task. This allows separate processing of stars and background objects, or simply leaving out the stars altogether. StarXTerminator is a tool to remove stars from astronomical photographs that works in Photoshop and PixInsight. Hover over the photograph to see the original. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |