MNFNR

Description

Attempts to remove noise in a single image band using a procedure based on the Maximum Noise Fraction transformation.

Parameters

Name	Type	Caption	Length	Value range
FILE *	String	Input file name	1 - 192
DBIC	Integer	Input raster channel(s)	0 -
WLENINT	Float	Wavelength interval	0 - 2
VALONLY	String	Valid bands only	0 - 3	YES | NO Default: NO
SAMPINT	Integer	Sampling interval	0 - 2	1 - Default: 1,1
NOISCHN *	Integer	Channel containing noisy band	1 - 1	1 -
REPORT	String	Report mode	0 - 192	Quick links
MONITOR	String	Monitor mode	0 - 3	ON, OFF Default: ON

* Required parameter

Parameter descriptions

FILE

Specifies the name of the image file containing the noisy image channel to be replaced.

DBIC

Specifies the input channel(s) to be used for the noise reduction transformation.

Ranges of channels or segments can be specified with negative values. For example, {1,-4,10} is internally expanded to {1,2,3,4,10}. When you are not specifying a range in this way, only 48 numbers can be specified explicitly.

WLENINT

Specifies that the selected bands are to be restricted to those whose center wavelength is either inside or outside a closed interval, specified in nanometers. By default, no restriction is applied.

This parameter has no effect if the input file contains no band center wavelength metadata.

VALONLY

Specifies whether the selected bands are to be restricted to those with "plot" or "bmask" (begin mask) quality values. The default is NO.

This parameter has no effect if the input file contains no band-validity metadata.

SAMPINT

Specifies the X and Y sampling interval within the specified input window.

NOISCHN

Specifies the input channel containing the noisy band to correct.

REPORT

Specifies where to direct the generated report.

Available options are:

• TERM: generates a report on the terminal (default)
• DISK: generates a report on file "IMPRPT.LST"
• OFF: turns off report generation
• <filename>: appends a report to the specified file

MONITOR

The program progress can be monitored by printing the percentage of processing completed. A system parameter, MONITOR, controls this activity.

Available options are:

• ON: Turns the monitor ON (default)
• OFF: Turns the monitor OFF (recommended if running in batch or background mode)

Details

MNFNR is typically used in a case where a set of image bands contains one band that is considered to have significantly more noise than the others, and it is desirable to transform that band such that its noise content is close to that of the other bands. In this case, it is not necessary to know the noise variance in any band in order to define the MNF transformation.

The application of MNFNR is equivalent to replacing the noisy band (NOISCHN) with the linear combination of the other bands that best approximates the noisy band, in the least-squares sense.

MNFNR performs the same computation whether or not the specified noisy channel (NOISCHN) is included in those specified with DBIC.

MNFNR may be run multiple times to attempt noise removal on multiple bands of a data set. In each run, only one of the noisy bands can be specified as input (NOISCHN and DBIC).

Example

This example demonstrates noise-reduction for channels 107 to 113 of a copy of cuprad.pix. Channels 91 to 106 are selected as the basis of the correction because they visually appear to be highly correlated.

EASI>file	=	"cuprad_copy.pix"
EASI>dbic	=	(91, 106)
EASI>wlenint	=		! no wavelength interval restriction
EASI>valonly	=		! no band validity restriction
EASI>sampint	=		! no subsampling
EASI>noischn	=	107

EASI>RUN MNFNR

Algorithm

The details of the computation used in program MNFNR may be obtained from Section III.A of the following paper:

Green, A. A., M. Berman, P. Switzer, and M. D. Craig, "A Transformation for Ordering Multispectral Data in Terms of Image Quality with Implications for Noise Removal", IEEE Transactions on Geoscience and Remote Sensing, Vol. 26, No. 1 (1988), pp.65-74.

References

Green, A. A., M. Berman, P. Switzer, and M. D. Craig, "A Transformation for Ordering Multispectral Data in Terms of Image Quality with Implications for Noise Removal", IEEE Transactions on Geoscience and Remote Sensing, Vol. 26, No. 1 (1988), pp.65-74.