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eyes:logics:fourierprocesses [2017/06/08 13:37] jschlie1 created |
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| - | ====== Template Logic Description ====== | + | ====== FourierProcesses ====== |
| - | THIS position should be used for a brief introduction (max 2 sentences!) of the logic, stating WHAT and WHY it is doing something. | + | The processes in this logic provide a variety of calculations that include Fourier transformations in some way. |
| ===== 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 usage of this logic is fairly simple: the input data are subjected to the selected algorithm and are output afterwards. Therefore, only one input and output are necessary/provided and no further information on I/O is given below. |
| - | ===== Example ==== | + | ===== Processors ===== |
| - | 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. | + | ==== Bispectrum ==== |
| + | Calculates a [[http://en.wikipedia.org/wiki/Bispectrum|Bispectrum]] for the two input image stacks, which is defined as the third order cumulant-generating function: | ||
| - | ===== Modes/Processes ===== | + | B(f1,f2) = F*(f1+f2).F(f1).F(f2) |
| - | ==== thisIsTheNameOfMode1 ==== | + | |
| - | 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. | + | where f1 and f2 are the input images , F is an images' Fourier Transform and F* its conjugate. |
| + | |||
| + | For every pair of images, a bispectrum is generated. While both inputs can have different sizes, the amount of generated bispectra is equal to the maximum number of unambigous image pairs that can be formed, which is the size of the smaller of the two stacks. | ||
| + | |||
| + | Also, both images need to have the same dimensions (and dimensionality). | ||
| + | |||
| + | ==== Center corrected power spectrum ==== | ||
| + | Use this module to generate power spectra of single particles used as input data during CTF correction. Note: For K2 Particles, turn off the highpass filter for power spectra. | ||
| |< 100% 30% >| | |< 100% 30% >| | ||
| - | ^ Parameters ^ Description ^ | + | ^ Parameters ^ Description ^ |
| - | | Some changeable parameter | Description of this parameter | | + | | Output size | Width and height size of the power spectra. The new size is achieved by cropping (this changes the pixel size of the power spectra!) [in pixel] | |
| - | | -> and its sub-parameter | more description | | + | | Highpass value | Gaussian highpass filter value used directly on the input data. [0…1] | |
| - | | Next main parameter | and more more more | | + | | Apply softmask | If checked, applies a circular soft mask to the input images. | |
| - | | -> and its sub-parameter | ... descriptions | | + | | Apply highpass filter | If checked, applies a highpass filter to the computed power spectra. | |
| + | | Low freq cutoff | If Apply highpass filter to power spectra is checked, this value defines the Gaussian highpass value used to filter the computed power spectra. [0…1] | | ||
| + | | Constant value to add | This value is added to each pixel of the power spectrum. [a floating point number] | | ||
| + | | Logarithmic power spectrum | If checked, calculates the pixel values of the power spectrum on a logarithmic scale. | | ||
| + | | Filtering type | Select, whether a cosine- or Gaussian-shaped transition curve should be used for filtering. | | ||
| + | |||
| + | ==== Combine/Extract XX of YY image ==== | ||
| + | These three processes are closely related: | ||
| + | * Extract imaginary part of complex image | ||
| + | * Extract real part of complex image | ||
| + | * Combine parts of complex image | ||
| + | |||
| + | Theses processes can be used to extract one of the two parts of a Fourier transformed image or combine the formally extracted parts back together into a whole complex Fourier space image. This is necessary, since it is not possible, to visualize a Fourier transformed image consisting of both, imaginary and real part. To produce a complex Fourier transformed image, use [[#FT XX to YY]]. | ||
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| ^ Input ^ Description ^ | ^ Input ^ Description ^ | ||
| - | | FirstInput | Input Description 1 | | + | | Input1 | This needs to be a Fourier transformed image or stack of images. | |
| - | | SecondInput | Input Description 2 | | + | | Input2 | If two parts of a complex image shall be combined, Input1 needs to be the real image while Input2 needs to be the imaginary part. | |
| - | | //ThirdInput// | Input Description 3: Optional Input in Italic | | + | |
| - | |< 100% 30% >| | + | ==== FFT resize ==== |
| - | ^ Output ^ Description ^ | + | Scales the real image by padding/enlarging the image in Fourier space. |
| - | | FirstOutput | Output Description | | + | |
| |< 100% 30% >| | |< 100% 30% >| | ||
| - | ^ New/Changed Header Values ^ Description ^ | + | ^ Parameters ^ Description ^ |
| - | | headerValue1 | what does it say? how is it changed? | | + | | Pad size | Scaling factor. | |
| - | | 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 ==== | + | ==== FT XX to YY ==== |
| - | 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. | + | This processor performs Fourier transformations either from real-to-complex (forward), complex-to-real (backward) or complex-to-complex images. Caution: Due to algorithmic reasons, every pixel value of the images is scaled by the factor sidelength x sidelength. |
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| - | ^ Parameters ^ Description ^ | + | ^ Parameters ^ Description ^ |
| - | | Some changeable parameter | Description of this parameter | | + | | Dimensionality | Dimensionality (2 or 3) of the input | |
| - | | -> and its sub-parameter | more description | | + | | FT direction [0 = fw, 1 = bw] | For complex-to-complex transformation, the direction needs to be given | |
| - | | Next main parameter | and more more more | | + | |
| - | | -> and its sub-parameter | ... descriptions | | + | ==== Fourier coarse ==== |
| + | This processor coarses images, this is performed in Fourier space. This allows floating point numbers to be used as coarse factors. | ||
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| - | ^ Input ^ Description ^ | + | ^ Parameters ^ Description ^ |
| - | | FirstInput | Input Description 1 | | + | | Coarse factor | The coarse factor used to calculate the new image size (oldSize / coarseFactor = newSize). | |
| - | | SecondImput | Input Description 2 | | + | |
| - | | ThridImput | Input Description 1 | | + | ==== Fourier ring correlation ==== |
| + | The Fourier ring correlation represents the 2-dimensional version of a [[https://en.wikipedia.org/wiki/Fourier_shell_correlation|Fourier shall correlation (FSC)]]. Here, the two input images are Fourier transformed and correlated, which is output as a line plot. | ||
| + | |||
| + | ==== Micrograph power spectrum ==== | ||
| + | This processor computes the [[http://en.wikipedia.org/wiki/Spectral_density#Power_spectral_density|power spectrum]] of EM micrograph data by splitting it in multiple smaller images to enhance contrast and visibility of Thon rings. It only works properly on even sized images. | ||
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| - | ^ Output ^ Description ^ | + | ^ Parameters ^ Description ^ |
| - | | FirstOutput | Output Description | | + | | No of images cut out | Sets the number of images cut out in each direction. | |
| + | | Size of cut images | Size of cut out images. Needs to be smaller than the input images. This is also the size of the output images. | | ||
| + | |||
| + | ==== Power spectrum ==== | ||
| + | This processor computes the [[http://en.wikipedia.org/wiki/Spectral_density#Power_spectral_density|power spectrum]] or phase spectrum of real or complex image data. Input images need to meet the following requirements: Height == Width, Height % 2 == 0. | ||
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| - | ^ New/Changed Header Values ^ Description ^ | + | ^ Parameters ^ Description ^ |
| - | | headerValue1 | what does it say? how is it changed? | | + | | Automatic level adjustment | Enables auto level adjustment, ignoring the 20% most outlying pixels and scaling accordingly. | |
| - | | headerValue2 | what does it say? how is it changed? | | + | | Logarithmic | Enables scaling all power spectrum pixel values logarithmically. | |
| - | | headerValue3 | what does it say? how is it changed? | | + | | Display mode | Selects the desired display mode: phase = displays phase information; power = displays power spectrum. | |
| - | | headerValue4 | what does it say? how is it changed? | | + | | Skip Fourier transformation | This value enables skipping the Fourier transformation. Use this option when input data is already in Fourier space. | |
| - | ===== 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. | ||