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or the analysis of image processing routines one often needs simulated - pseudoexperimental - images with known properties (e.g. angular orientation or the structural state of the particle image), but additional noise or random orientations. Test Image allows to create such images.
This logic creates simulated pseudoexperimental images. It can randomly add noise and shift and rotate images. The logic does not generate an image (like a disk) on its own without an input; for this purpose use the logic: CreateImage.
Here, a very specific example should be given/described. In the future, this can be supported by screenshots etc.. For the moment, give an example easy enough for the user to understand, but specific enough to elaborate why a given parameter is a good set for this very situation.
Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.
| Parameters | Description |
| Some changeable parameter | Description of this parameter |
| → and its sub-parameter | more description |
| Next main parameter | and more more more |
| → and its sub-parameter | … descriptions |
| Input | Description |
| FirstInput | Input Description 1 |
| SecondInput | Input Description 2 |
| ThirdInput | Input Description 3: Optional Input in Italic |
| Output | Description |
| FirstOutput | Output Description |
| New/Changed Header Values | Description |
| headerValue1 | what does it say? how is it changed? |
| headerValue2 | what does it say? how is it changed? |
| headerValue3 | what does it say? how is it changed? |
| headerValue4 | what does it say? how is it changed? |
Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.
| Parameters | Description |
| Some changeable parameter | Description of this parameter |
| → and its sub-parameter | more description |
| Next main parameter | and more more more |
| → and its sub-parameter | … descriptions |
| Input | Description |
| FirstInput | Input Description 1 |
| SecondImput | Input Description 2 |
| ThridImput | Input Description 1 |
| Output | Description |
| FirstOutput | Output Description |
| New/Changed Header Values | Description |
| headerValue1 | what does it say? how is it changed? |
| headerValue2 | what does it say? how is it changed? |
| headerValue3 | what does it say? how is it changed? |
| headerValue4 | what does it say? how is it changed? |
In this paragraph, the “HOW a logic works under the hood” and WHY someone should use it can be elaborated with higher detail. Describes a scenario in an image processing workflow where this logic can be used to solve the resulting problem. Also, wikipages, publications or anything else describing the theory behind an algorithm should be linked here, if applicable.