SunPy image¶
The image submodule contains routines to process images (i.e. numpy
arrays).
The routines in this submodule are generally exposed through map-specific
functions in other places.
sunpy.image Package¶
sunpy.image.resample Module¶
Image resampling methods.
Functions¶
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Returns a new |
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Re-shape the two dimension input image into a a four dimensional array whose first and third dimensions express the number of original pixels in the “x” and “y” directions that form one superpixel. |
sunpy.image.transform Module¶
Functions for geometrical image transformation and warping.
Functions¶
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Rotates, shifts and scales an image. |
sunpy.image.coalignment Module¶
This module provides routines for the coalignment of images and
mapsequences
.
Currently this module provides image coalignment by template matching. Which is partially inspired by the SSWIDL routine tr_get_disp.pro.
In this implementation, the template matching is handled via the scikit-image
routine skimage.feature.match_template
.
References
- J.P. Lewis, Fast Template Matching, Vision Interface 95, Canadian Image
Processing and Pattern Recognition Society, Quebec City, Canada, May 15-19, 1995, p. 120-123 http://www.scribblethink.org/Work/nvisionInterface/vi95_lewis.pdf.
Functions¶
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Calculates the pixel shift required to put the template in the “best” position on a layer. |
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Clips off the “y” and “x” edges of a 2D array according to a list of pixel values. |
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Return the upper and lower clipping values for the “y” and “x” directions. |
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Calculate the correlation array that describes how well the template matches the layer. |
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Calculate an estimate of the location of the peak of the correlation result in image pixels. |
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Estimate the location of the maximum of a fit to the input array. |
Find the location of the turning point for a parabola |
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Issue a warning if there is any nonfinite entry in the layer or template images. |
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Apply a set of pixel shifts to a |
Co-register the layers in a |
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Calculate the arcsecond shifts necessary to co-register the layers in a |