fixnoisex -- Create a fixed-pattern noise image.
fixnoisex input output
The fixed-pattern noise in a Faint Object Camera (FOC) image is any fine-scale pattern that is constant from one image to another for a given detector, image size, and offset.
This task will create a fixed-pattern noise image by smoothing a given flat-field image to remove fine details, leaving only large-scale features; then divide this into the original image, giving an image with only the fine-scale features, presumed to be fixed-pattern noise. If the input and output lists contain more than one file name, then the smoothed and divided images are averaged to reduce the effect of photon statistics and other nonfixed noise contributions. (This task is a script, which uses tasks in the images package.)
The distinction between fixed-pattern noise and format-dependent noise is blurred and, in principle, the two should be combined.
- input = test [file name template]
- File names of the flat-field illumination images from which the fixed-noise pattern will be generated.
- output = test [file name template]
- File names for the fixed-pattern noise images produced by fixnoisex.
- smoothing = boxcar [string, allowed values: boxcar | convolve |
- median | mode]
The type of smoothing function to be applied. If 'smoothing = convolve', the image is convolved with the values given by the kernel parameter.
- (xwindow = 13) [integer, min=1]
- The X side of box---in pixels---for smoothing.
- (ywindow = 13) [integer, min=1]
- The Y side of box---in pixels---for smoothing.
- (kernel = ) [string]
- This parameter is used only if smoothing = convolve, in which case this parameter is the name of the kernel to be used. The kernel parameter accepts either a text file name or a string listing the kernel elements. In the latter case, the elements are separated by whitespace or commas, rows are separated by semicolons, and elements are assumed to be in row order. If kernel is a text file, however, the last row of the kernel is the first row of the text file.
- (title = "fix pattern noise") [string]
- The title for the output image.
- (low_reject = 0.0) [real]
- Lower threshold for rejecting low-valued pixels when calculating the average (low_reject and high_reject apply only when averaging images, not when calculating the average for smoothing). If low_reject is less than 1, it will be treated as a fraction of the total number of pixels that are to be ignored. If low_reject is greater than 1, then that number of values at the low end will be ignored. For example, 'low_reject = 8.' will ignore the lowest 8 values, whereas low_reject = .8 will ignore the lowest 80% of the pixels.
- (high_reject = 0.0) [real]
- Upper threshold for rejecting high-valued pixels when calculating the average (low_reject and high_reject apply only when averaging images, not when calculating the average for smoothing). If high_reject is less than 1, it will be treated as a fraction of the total number of pixels that are to be ignored. If high_reject is greater than 1, then that number of values at the high end will be ignored.
- (boundary = nearest) [string, allowed values: nearest | constant |
The type of boundary extension to be used.
- (constant = 0.) [real]
- Constant for constant boundary extension. This parameter is ignored if "constant" is not passed to the boundary parameter.
- (zerodiv = 0.) [real]
- Value that is to be assigned to a quotient in case of division by zero. See help for the images.imdivide task for more information on this parameter.
- (verbose = no) [boolean]
- Display details of the operations on the terminal screen?
- (inimglist) [structure]
- Task-defined parameter containing the images being processed.
1. Use boxcar smoothing to make the fixed-pattern noise image.
fo> fixnoisex @in @out boxcar xwindow=21 ywindow=21
2. Use convolution to smooth image, note the normalized kernel.
fo> fixnoisex @in @out convolve xwindow=3 ywindow=3 \ kernel=".1,.1,.1;.1,.2,.1;.1,.1,.1"
This task was written by David Giaretta.
Type "help images.convolve" for information about convolution.
Type "help images.imdivide" for more information about zero replacement.