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eyes:logics:optimizereferences [2017/06/08 13:14]
ksingh2
eyes:logics:optimizereferences [2017/06/12 18:36] (current)
jschlie1
Line 1: Line 1:
-====== ​Optimize References ​====== +====== ​OptimizeReferences ​====== 
-THIS position should be used for brief introduction ​(max 2 sentences!of the logicstating WHAT and WHY it is doing something.+This logic aligns class averages so that they share the same mutual orientation.  
 +After classification step different classes might contain the same view, but rotated in the image plane (i.e. different α-angles), so an alignment ​is needed to optimize the class averages before using them as references for image alignment.
  
 ===== 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. +The quality ​of the output heavily depends on the quality ​of the first class average chosen - preferablyit should ​show enough details of the molecule or complex and be surrounded ​by a black rim.  
- +The optimal values suggested ​for radius parameter are around 0.8-0.9.
-===== Example ==== +
-Herea 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 given parameter is a good set for this very situation+
- +
-===== Modes/​Processes ===== +
-==== thisIsTheNameOfMode1 ==== +
-Here, a short introduction ​for the given mode should be placedAgain, state WHAT and WHY this mode us useful in not more than 2 sentences.+
  
 +===== Parameters =====
 |< 100% 30% >| |< 100% 30% >|
 ^ Parameters ​                ^ Description ​    ^ ^ Parameters ​                ^ Description ​    ^
-Some changeable parameter  ​Description of this parameter | +Correlation Function ​      The correlation function that is optimized during the image alignment ​
-| -> and its sub-parameter ​  | more description | +Fraction ​                  The maximal fraction of the image that will be shifted relative to the reference image during the alignment ​
-| Next main parameter ​       | and more more more | +Interpolation ​             ​Defines ​the interpolation function used to get the value between two neighbouring pixels ​
-| -> and its sub-parameter ​  | ... descriptions | +Radius ​                    The value of Circular Mask Fraction (this fraction of image dimension will be used as diameter of the circle cut from the image for cf calculations)
- +Sampling ​                  The maximal fraction of the image shifted during the alignment relative to the reference image |
-|< 100% 30% >| +
-^ Input   ^ Description ^ +
-| FirstInput ​ | Input Description 1 | +
-| SecondInput | Input Description 2 | +
-| //​ThirdInput// ​ | Input Description 3: Optional Input in Italic | +
- +
-|< 100% 30% >| +
-^ Output ​  ^ Description ^ +
-| FirstOutput | Output Description | +
- +
-|< 100% 30% >| +
-^ 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? | +
- +
-==== thisIsTheNameOfMode2 ==== +
-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. +
- +
-|< 100% 30% >| +
-^ 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 | +
- +
-|< 100% 30% >| +
-^ Input   ^ Description ^ +
-| FirstInput ​ | Input Description 1 | +
-| SecondImput | Input Description 2 | +
-| ThridImput ​ | Input Description 1 | +
- +
-|< 100% 30% >| +
-^ Output ​  ^ Description ^ +
-| FirstOutput | Output Description | +
- +
-|< 100% 30% >| +
-^ 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? ​|+
  
 ===== Concept ===== ===== Concept =====
-In this paragraph, the "HOW a logic works under the hood" ​and WHY someone should use it can be elaborated with higher detailDescribes a scenario in an image processing workflow where this logic can be used to solve the resulting problemAlso, wikipages, publications or anything else describing ​the theory behind an algorithm should be linked here, if applicable.+The logic takes a stack of class average images as input. It applies the circular mask of radius changed by parameter '​Radius'​ to every image, so that only the defined circle ​and not the surrounding noise will be used for correlation calculationsThen the logic aligns every image to the first one by shifting them in [[https://​en.wikipedia.org/​wiki/​Polar_coordinate_system|polar coordinates]] (that corresponds to rotation of image in Cartesian coordinates) and maximizing ​the correlation function