FGAMMA

Description

FGAMMA performs gamma maximum-a-posteriori (MAP) filtering on image data. The gamma MAP filter is primarily used on radar data to remove high-frequency noise (speckle) while preserving high-frequency features (edges).

Parameters

Name	Type	Length	Value range
Input: Input detected SAR image *	Raster port	1 -
Mask: Area mask	Bitmap port	0 - 1
Output: Output filtered image *	Raster port	1 - 1024
Filter X Size	Integer	0 - 2	Default: 7
Filter Y Size	Integer	0 - 1	Default: 7
Number of Looks	Float	0 - 1	1 - 100 Default: 1
Image Units	String	0 - 1	Amplitude | Power Default: Amplitude

* Required parameter

Parameter descriptions

Input: Input detected SAR image

Specifies the image layers to be filtered.

Mask: Area mask

Optionally specifies the bitmap that defines the area to be processed within the input raster. If this parameter is not specified, the entire layer is used by default. For a bitmap mask, you must specify the bitmap segment that you want to use. All of the pixels within the specified segment, having a pixel value of 1, define the area to be processed.

Only the area under the mask is written to the output.

Output: Output filtered image

Specifies the output channel(s) to receive the filtered results. If the specified output file already exists, the filtered channels will be appended to the existing file. If the output file does not already exist, a new file is created.

Filter X Size

Optionally specifies the horizontal size of the filter, in pixel units. This value must be a positive odd integer. The default value is 7 pixels.

Filter Y Size

Optionally specifies the vertical size of the filter, in pixel units. This value must be a positive odd integer. The default value is 7 pixels.

Number of Looks

Optionally specifies the effective number of looks of the SAR image. This is used to derive noise variance. Over homogeneous areas, the effective number of looks can be computed as the mean value squared divided by the variance (for amplitude data) or the mean divided by the standard deviation (for power data). By adjusting this parameter value, you can control the amount of smoothing applied to the image.

Acceptable values are 1 to 100. The default value of 1 is appropriate for single-look data and specifies maximum smoothing correction to the image.

Instead of 1, the default value of this parameter will be the file level metadata value for 'NumLooks' if this metadata exists.

Image Units

Optionally specifies the image format of the SAR image, which defines how the correction factor should be computed. By default, the image is assumed to be in amplitude units.

Image units can be "Amplitude" (or equivalently "AMP") or "Power" (or equivalently "POW").

Details

FGAMMA is used primarily to filter speckled radar data. The filter smoothes the image data, without removing edges or sharp features in the images.

The Gamma MAP filter was first proposed by Kuan. To apply it, the a priori knowledge of the probability density function of the scene is required. Although the scene reflectivity is assumed to be Gaussian distributed, this is not realistic because it implicitly assumes a negative reflectivity. Lopes modified the Kuan Map filter by assuming a gamma distributed scene and setting up two thresholds.

Algorithm

The Gamma Map filter was first proposed by Kuan. To apply it, the a priori knowledge of the probability density function of the scene is required. Although the scene reflectivity was assumed to be Gaussian distributed, this is not quite realistic because it implicitly assumes a negative reflectivity. Lopes modified the Kuan Map filter by assuming a gamma-distributed scene and setting up two thresholds.

FGAMMA performs spatial filtering on each individual pixel in an image using the gray-level values in a window surrounding each pixel. The dimensions of the filter must be odd, and can be from 3x3 to 11x11 pixels. All pixels are filtered. To filter pixels located near edges of the image, edge pixels are replicated to provide sufficient data.

         +----------+
         | a1 a2 a3 |
         | a4 a5 a6 |     <---  Filter window 3 X 3
         | a7 a8 a9 |
         +----------+

The resulting gray-level value R for the smoothed pixel is:

R = I                    for Ci less than or equal to Cu
R = (B*I + SQRT(D))/(2*ALFA)  for Cu < Ci < Cmax
R = CP                   for Ci greater than or equal to Cmax

For amplitude images, each gray-level will be squared and the square root will be applied to the final result.

FGAMMA also uses a method described in "Adaptive Speckle Filters and Scene Heterogeneity" (see References).

This method removes isolated pixels (pixels of very high or very low value) in homogeneous areas. All pixels are filtered. To filter pixels located near the edges of the image, edge-pixel values are replicated to provide sufficient data.

References

A. Lopes, E. Nezry, R. Touzi, and H. Laur, "Structure detection and statistical adaptive speckle filtering in SAR images", International Journal of Remote Sensing, Vol. 14, No. 9, pp. 1735-1758, 1993.

A. Lopes, R. Touzi, and E. Nezry, "Adaptive Speckle Filters and Scene Heterogeneity", IEEE Transactions on Geoscience and Remote Sensing, Vol 28, No. 6, November 1990.

Zhenghao Shi and Ko B. Fung, 1994, "A Comparison of Digital Speckle Filters", Proceedings of IGRASS 94, August 8-12, 1994.