MEDIAN

Smooths a two-dimensional data array using a weighted median filter

Description:

This task filters the two-dimensional data array in the input NDF  structure with a Weighted Median Filter (WMF) in a 3-by-3-pixel kernel to create a new NDF. There are a number of predefined weighting functions and parameters that permit other symmetric weighting functions. See Parameter MODE and the topic “User-defined Weighting Functions”.

A threshold for replacement of a value by the median can be set. If the absolute value of the difference between the actual value and the median is less than the threshold, the replacement will not occur. The array boundary is dealt by either pixel replication or a reflection about the edge pixels of the array.

The WMF can be repeated iteratively a specified number of times, or it can be left to iterate continuously until convergence is achieved and no further changes are made to the data. In the latter case a damping algorithm is used if the number of iterations exceeds some critical value, which prevents the result oscillating between two solutions (which can sometimes happen). When damping is switched on data values are replaced not by the median value, but by a value midway between the original and the median.

Bad pixels are not included in the calculation of the median. There is a defined threshold which specifies minimum-allowable median position as a fraction of the median position when there are no bad pixels. For neighbourhoods with too many bad pixels, and so the median position is too small, the resulting output pixel is bad.

Usage:

median in out [mode] [diff] [bound] [numit] [corner] [side] [centre]

Parameters:

BOUND = LITERAL (Read)
Determines the type of padding required at the array edges before the filtering starts. The alternatives are described below.
"Replication" –- The values at the edge of the data array are replicated into the padded area. For example, with STEP=2 one corner of the original and padded arrays would appear as follows:

corner of original array: 1 1 1 1 1 1 2 2 2 2 1 2 3 3 3 1 2 3 4 4 1 2 3 4 5   corresponding corner of padded array: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 1 1 1 2 3 3 3 1 1 1 2 3 4 4 1 1 1 2 3 4 5

"Reflection" –- The values near the edge of the data array are reflected about the array’s edge pixels. For example, with STEP=2 one corner of the original and padded arrays would appear as follows:

corner of original array: 1 1 1 1 1 1 2 2 2 2 1 2 3 3 3 1 2 3 4 4 1 2 3 4 5   corresponding corner of padded array: 3 2 1 2 3 3 3 2 2 1 2 2 2 2 1 1 1 1 1 1 1 2 2 1 2 2 2 2 3 2 1 2 3 3 3 3 2 1 2 3 4 4 3 2 1 2 3 4 5

["Replication"]

CENTRE = _INTEGER (Read)
Central value for weighting function, required if MODE = 1. It must be an odd value in the range 1 to 21. [1]
CORNER = _INTEGER (Read)
Corner value for weighting function, required if MODE = 1. It must be in the range 0 to 10. [1]
DIFF = _DOUBLE (Read)
Replacement of a value by the median occurs if the absolute difference of the value and the median is greater than DIFF. [0.0]
IN = NDF (Read)
NDF structure containing the two-dimensional data array to be filtered.
ITERATE = LITERAL (Read)
Determines the type of iteration used. The alternatives are described below.
"Specified" –- You specify the number of iterations at each step size in the Parameter NUMIT.
"Continuous" –- The filter iterates continuously until convergence is achieved and the array is no longer changed by the filter. A damping algorithm comes into play after MAXIT iterations, and the filter will give up altogether after MAXIT × 1.5 iterations (rounded up to the next highest integer).

"Continuous" mode is recommended only for images which are substantially smooth to start with (such as a sky background frame from a measuring machine). Complex images may take many iterations, and a great deal of time, to converge. ["Specified"]

MAXIT = _INTEGER (Read)
The maximum number of iterations of the filter before the damping algorithm comes into play, when ITERATE = "Continuous". It must lie in the range 1 to 30. [10]
MEDTHR = _REAL (Read)
Minimum-allowable actual median position as a fraction of the median position when there are no bad pixels, for the computation of the median at a given pixel. [0.8]
MODE = _INTEGER (Read)
Determines type of weighting used, 1 allows you to define the weighting, and 0 to 7 the predefined filters. The predefined modes have the following weighting functions:
0 : 1 1 1 1 : 0 1 0 2 : 1 0 1 3 : 1 1 1 1 1 1 1 1 1 0 1 0 1 3 1 1 1 1 0 1 0 1 0 1 1 1 1 4 :0 1 0 5 :1 0 1 6 :1 2 1 7 :1 3 1 1 3 1 0 3 0 2 3 2 3 3 3 0 1 0 1 0 1 1 2 1 1 3 1

[0]

NUMIT = _INTEGER (Read)
The specified number of iterations of the filter, when ITERATE="Specified". [1]
OUT = NDF (Write)
NDF structure to contain the two-dimensional data array after filtering.
SIDE = _INTEGER (Read)
Side value for weighting function, required if MODE = 1. It must be in the range 0 to 10. [1]
STEP() = _INTEGER (Read)
The spacings between the median filter elements to be used. The data may be filtered at one particular spacing by specifying a single value, such as STEP=4, or may be filtered at a whole series of spacings in turn by specifying a list of values, such as STEP=[4,3,2,1]. There is a limit of 32 values. [1]
TITLE = LITERAL (Read)
The title for the output NDF. A null value will cause the title of the NDF supplied for parameter IN to be used instead. [!]

Examples:

median a100 a100med
This applies an equally weighted median filter to the NDF called a100 and writes the result to the NDF a100med. It uses the default settings, which are a single step size of one pixel, and a difference threshold of 0.0. The task pads the array by replication to deals with the edge pixels, and runs the filter once only.
median a100 a100med bound=ref
As in the previous example except that it uses reflection rather than replication when padding the array.
median abc sabc mode=3 step=4 diff=1.0 numit=2
This applies a median filter to the NDF called abc with a 1 1 1 1 3 1 1 1 1 weighting mask (MODE=3), a step size of 4 pixels (STEP=4) and a difference threshold of 1.0 (DIFF=1.0). It runs the filter twice (NUMIT=2) and writes the result to the NDF called sabc.
median abc sabc mode=3 step=[4,3,2,1] diff=1.0 numit=2
This applies a median filter as in the previous example, only this time run the filter at step sizes of 4, 3, 2, and 1 pixels, in that order (STEP=[4,3,2,1]). It runs the filter twice at each step size (NUMIT=2). Note that the filter will be run a total of eight times (number of step sizes times the number of iterations).
median in=spotty step=[4,3,2,1] iterate=cont maxit=6 out=clean
This applies a median filter to the NDF called spotty with the default settings for the mode and difference threshold. It runs the filter at step sizes of 4, 3, 2 and 1 pixels, operating continuously at each step size until the result converges (ITERATE=CONT). Damping will begin after 6 iterations (MAXIT=6), and the filtering will stop regardless after 10 iterations (1 + INT(1.5 MAXIT)). Note that the filter will run an indeterminate number of times, up to a maximum of 40 (number of step sizes × maximum number of iterations), and may take a long time. The resultant data array are written to the NDF called clean.

User-defined Weighting Functions

Parameters CORNER, SIDE, and CENTRE allow other symmetric functions in addition to those offered by MODE=0  to 7. A step size has to be specified too; this determines the spacing of the elements of the weighting function. The data can be filtered at one step size only, or using a whole series of step sizes in sequence. The weighting function has the form:
%CORNER . %SIDE . %CORNER . . . %SIDE . %CENTRE . %SIDE . . . %CORNER . %SIDE . %CORNER

The . Indicates that the weights are separated by the stepsize-minus-one zeros.

Related Applications

KAPPA: BLOCK, CONVOLVE, FFCLEAN, GAUSMOOTH; ESP: FASTMED; FIGARO: ICONV3, ISMOOTH, IXSMOOTH, MEDFILT.

Implementation Status: