![]() Click "Preview" to open the preview box - zoom in to see the changes in detail.Move to the next tab - "Noise Filter Settings".Profile Match should be at least 90% and Profile Quality should be at least 80% for best results. To verify your profile completed successfully, look at Profile Quality and match on the bottom-right of Neat Image.For best results, you might want to manually select a blank patch that is somewhat dark (click and drag a box on the image) - try to avoid an area with actual detail or varying brightness/color (as this will confuse the profiler), bright areas (since these don't have much noise), or near-black areas (since the noise deviation is too low to detect). Profiling the image takes a blank, detail-less area, and analyzes the noise characteristics of the image (this is how the program differentiates between pixel variations that are detail and not noise). ![]() Profile your image by clicking "Auto profile".Move to the next tab - Device Noise Profile.Noiseware (Windows): Download "Noiseware Community Edition Standalone 2.6"Īfter installing the program, you can follow these steps for processing your images for noise reduction (written for Neat Image, but this and the other programs should be intuitive - email if you have any problems).Noise Ninja (Windows/Mac/Linux): Download the appropriate version for your operating system.Neat Image for Photoshop (Mac): Download "Demo plug-in /Mac Universal Binary" (this is a plugin for Photoshop only).Neat Image (Windows): Download "Demo edition setup".Noiseware is also a free program (less controls, but more automatic than Neat Image), but for Windows only. Otherwise, you can try Noise Ninja, which runs on Windows, Mac OS, and Linux, but won't let you save photos without a watermark. If you are running Mac OS and have Photoshop or Photoshop Elements, you can download a freeware plugin of Neat Image. Neat Image is a freeware program for non-commercial use that can be downloaded below. The primary tools we'll be using is a noise reduction called Neat Image. This week's assignment is to try out a few of the noise reduction methods demonstrated in class on one (or more) of your high ISO images from the Week 5 or Week 6 assignments.
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