LSST Applications
21.0.0-172-gfb10e10a+18fedfabac,22.0.0+297cba6710,22.0.0+80564b0ff1,22.0.0+8d77f4f51a,22.0.0+a28f4c53b1,22.0.0+dcf3732eb2,22.0.1-1-g7d6de66+2a20fdde0d,22.0.1-1-g8e32f31+297cba6710,22.0.1-1-geca5380+7fa3b7d9b6,22.0.1-12-g44dc1dc+2a20fdde0d,22.0.1-15-g6a90155+515f58c32b,22.0.1-16-g9282f48+790f5f2caa,22.0.1-2-g92698f7+dcf3732eb2,22.0.1-2-ga9b0f51+7fa3b7d9b6,22.0.1-2-gd1925c9+bf4f0e694f,22.0.1-24-g1ad7a390+a9625a72a8,22.0.1-25-g5bf6245+3ad8ecd50b,22.0.1-25-gb120d7b+8b5510f75f,22.0.1-27-g97737f7+2a20fdde0d,22.0.1-32-gf62ce7b1+aa4237961e,22.0.1-4-g0b3f228+2a20fdde0d,22.0.1-4-g243d05b+871c1b8305,22.0.1-4-g3a563be+32dcf1063f,22.0.1-4-g44f2e3d+9e4ab0f4fa,22.0.1-42-gca6935d93+ba5e5ca3eb,22.0.1-5-g15c806e+85460ae5f3,22.0.1-5-g58711c4+611d128589,22.0.1-5-g75bb458+99c117b92f,22.0.1-6-g1c63a23+7fa3b7d9b6,22.0.1-6-g50866e6+84ff5a128b,22.0.1-6-g8d3140d+720564cf76,22.0.1-6-gd805d02+cc5644f571,22.0.1-8-ge5750ce+85460ae5f3,master-g6e05de7fdc+babf819c66,master-g99da0e417a+8d77f4f51a,w.2021.48
LSST Data Management Base Package
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Public Member Functions | |
def | find (self, maskedImage) |
def | run (self, maskedImage) |
Public Attributes | |
edges | |
lines | |
Static Public Attributes | |
ConfigClass = MaskStreaksConfig | |
Find streaks or other straight lines in image data. Nearby objects passing through the field of view of the telescope leave a bright trail in images. This class uses the Kernel Hough Transform (KHT) (Fernandes and Oliveira, 2007), implemented in `lsst.houghtransform`. The procedure works by taking a binary image, either provided as put or produced from the input data image, using a Canny filter to make an image of the edges in the original image, then running the KHT on the edge image. The KHT identifies clusters of non-zero points, breaks those clusters of points into straight lines, keeps clusters with a size greater than the user-set threshold, then performs a voting procedure to find the best-fit coordinates of any straight lines. Given the results of the KHT algorithm, clusters of lines are identified and grouped (generally these correspond to the two edges of a strea) and a profile is fit to the streak in the original (non-binary) image.
Definition at line 508 of file maskStreaks.py.
def lsst.pipe.tasks.maskStreaks.MaskStreaksTask.find | ( | self, | |
maskedImage | |||
) |
Find streaks in a masked image Parameters ---------- maskedImage : `lsst.afw.image.maskedImage` The image in which to search for streaks. Returns ------- result : `lsst.pipe.base.Struct` Result struct with components: - ``originalLines``: lines identified by kernel hough transform - ``lineClusters``: lines grouped into clusters in rho-theta space - ``lines``: final result for lines after line-profile fit - ``mask``: 2-d boolean mask where detected lines are True
Definition at line 530 of file maskStreaks.py.
def lsst.pipe.tasks.maskStreaks.MaskStreaksTask.run | ( | self, | |
maskedImage | |||
) |
Find and mask streaks in a masked image. Finds streaks in the image and modifies maskedImage in place by adding a mask plane with any identified streaks. Parameters ---------- maskedImage : `lsst.afw.image.maskedImage` The image in which to search for streaks. The mask detection plane corresponding to `config.detectedMaskPlane` must be set with the detected pixels. Returns ------- result : `lsst.pipe.base.Struct` Result struct with components: - ``originalLines``: lines identified by kernel hough transform - ``lineClusters``: lines grouped into clusters in rho-theta space - ``lines``: final result for lines after line-profile fit
Definition at line 573 of file maskStreaks.py.
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static |
Definition at line 526 of file maskStreaks.py.
lsst.pipe.tasks.maskStreaks.MaskStreaksTask.edges |
Definition at line 551 of file maskStreaks.py.
lsst.pipe.tasks.maskStreaks.MaskStreaksTask.lines |
Definition at line 552 of file maskStreaks.py.