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eyes:logics:optimizereferences [2017/06/08 15:29] vzinch [Concept] |
eyes:logics:optimizereferences [2017/06/12 15:18] vzinch [OptimizeReferences] |
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| ====== OptimizeReferences ====== | ====== OptimizeReferences ====== | ||
| - | This logic aligns the class averages so that they are in the same direction. | + | 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, so alignment is needed for the same views to look identical. | + | After a 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 ===== | ||
| Line 8: | Line 8: | ||
| - | ===== Example ===== | ||
| - | FIXME | ||
| ===== Process ===== | ===== Process ===== | ||
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| | Output | A set of aligned class averages | | | Output | A set of aligned class averages | | ||
| - | |< 100% 30% >| | ||
| - | ^ Written Header Values ^ Description ^ | ||
| - | | resolutionAt0.143 | Estimated resolution for FSC cut off at 0.143 | | ||
| - | | resolutionAt0.3 | Estimated resolution for FSC cut off at 0.3 | | ||
| - | | resolutionAt0.5 | Estimated resolution for FSC cut off at 0.5 | | ||
| - | | resolutionAt0.9 | Estimated resolution for FSC cut off at 0.9 | | ||
| - | | resolutionAt3Sigma | Estimated resolution for FSC cut off at 3 Sigma | | ||
| - | | resolution | Estimated resolution at the user chosen cut off value | | ||
| - | | maxResolution | Maximum resolution in the local map | | ||
| - | | meanResolution | Mean resolution in the local map | | ||
| - | | minResolution | Minimum resolution in the local map | | ||
| - | | resolutionVariance | Variance of the resolution in the local map | | ||
| - | | abscissaIsLogarithmical , abscissaMin, abscissaMax | For internal 1D viewer use only, to be hidden | | ||
| - | FIXME | ||
| ===== Concept ===== | ===== Concept ===== | ||
| - | 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 calculations. Then 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). | + | 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 calculations. Then 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. |