This page describes some concepts and terms that are helpful for getting the most out of Noise Ninja.
The user interface is annotated with "What's This?" pop-up help.
To use it, click on the "What's This?" button:
Then click on an item in the user interface to see a description. Alternatively,
move the mouse over an item and press the F2 key. Note that What's This help
is usually more detailed than the tooltips that display when you hover the mouse.
In addition, several tools and dialogs have Overview buttons that will display
summary information:
Most digital images are represented using the RGB color space, which decomposes each color into a red, green, and blue component. During filtering and profiling, Noise Ninja converts images into another color space called YCrCb. In this scheme, each color is represented as a luminance (brightness) value, a red-green chroma value, and a blue-yellow chroma value.
The luminance component normally contains the majority of actual information in an image. From an information-theoretic point of view, color adds relatively little information to an image. Another way of stating this is to say that color has a lot of redundancy in it -- nearby pixels tend to have the same color, so the color is not helping to distinguish them. In contrast, luminance information normally captures most of the edges, textures, and other detail in an image.
Not surprisingly, luminance noise and chroma noise tend to have different characteristics. By separating them, Noise Ninja can do a better job of filtering each type of noise.
There are a few places in the user interface where the YCrCb color space is exposed. One is in the profiling chart, where you can view noise levels for each YCrCb channel. Another is the channel selector in the main window, which allows you to view individual YCrCb or RGB color channels.
Noise reduction involves two distinct concepts. Profiling characterizes noise in an image. Generally, profiling describes how much noise is associated with different colors, tones, and spatial frequencies (resolutions). Filtering is the actual removal of noise. Filtering uses profiling information to estimate the amount of noise in the image, and it has additional parameters to control how aggressively the noise is suppressed.
In discussions of digital photography, you'll often hear the term "workflow". This simply refers to the steps that an image goes through, from the time it is exposed in the camera, to the point at which it is published. Workflow is different for every user and organization, and it can involve a variety of software applications and adjustments.
Noise Ninja is just one piece of the digital workflow. As such, a decision needs to be made about where it should be used within the overall workflow. Generally speaking, it is best to apply noise reduction as early as possible, before other adjustments have shifted pixel values and noise values around. For instance, histogram stretching, color balancing, and sharpening can distort noise levels and make it more difficult for Noise Ninja to remove noise. (Modest in-camera adjustments are usually not problematic, especially if you create noise profiles that account for them.) On the other hand, sometimes it is impractical to use Noise Ninja before other steps. In the end, it depends on your particular workflow, your objectives, and your preferences, and some experimentation may be required to find the optimal strategy.