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This logic uses the result of the PCA logic (the eigenvectors) to transform images into a new space spanned by these eigenvectors. I.e. Images can be represented as factors of eigenvectors, a so called linear combination.
Firstly PCA-transform can be used with any set of eigenvectors (as long as the x/y/z- dimensions of the PCA-input and the images used in the PCA transform are the same) to yield a set of linear factors. This is called a forward transform. Secondly, these linear factors can be used to generate images by multiplying eigenvectors and linear factors (back-transform).
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.