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eyes:logics:sumbyreference [2017/06/12 16:14] vzinch |
eyes:logics:sumbyreference [2017/06/12 16:57] flambre [SumByReference] |
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====== SumByReference ====== | ====== SumByReference ====== | ||
- | This logic takes a stack of images, that were previously aligned using some references (e.g. class averages), and sums the images that correspond to same references. This generates Alisums that inherit the Euler angles from the references, thus, can be directly used for 3D reconstruction. | + | This logic takes a stack of images, that were previously aligned using some references (e.g. class averages), and sums the images that correspond to the same references. This generates alisums that inherit the Euler angles from the references, thus, can be directly used for 3D reconstruction. |
===== Usage ===== | ===== Usage ===== | ||
- | Here, a general/generic description of HOW the logic is USED should be given. Try to be as general as possible, but also mention prerequisites, restrictions, advantages, requirements which are specific of this logic. Basically everything the user needs to know to successfully use this logic. | + | Using Ccc bounds parameter can filter out the images that were aligned worse or better than specified Ccc value. |
+ | Note that when Fill gaps option is not checked, the empty sums would just be skipped, and that will affect the imageID of the summed images. | ||
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===== Concept ===== | ===== Concept ===== | ||
- | 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. | + | Basically, this logic retrieves the information about which reference this image was aligned to and sums the images according to their references. |