FSTDDEV

Description

FSTDDEV applies a standard deviation speckle filter on a SAR image. This filter is primarily used on SAR 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 - 1
Filter X Size	Integer	0 - 1	1 \| 3 \| 5 \| 7 \| 9 \| 11 \| 13 \| 15 \| 17 \| 19 \| 21 \| 23 \| 25 \| 27 \| 29 \| 31 \| 33 Default: 7
Filter Y Size	Integer	0 - 1	1 \| 3 \| 5 \| 7 \| 9 \| 11 \| 13 \| 15 \| 17 \| 19 \| 21 \| 23 \| 25 \| 27 \| 29 \| 31 \| 33 Default: 7
Image Type	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 to receive the filtered results. If the specified output file already exists, the filtered channels are 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 an odd integer between 1 and 33. The default value is 7 pixels.

Filter Y Size

Optionally specifies the vertical size of the filter, in pixel units. This value must be an odd integer between 1 and 33. The default value is 7 pixels.

Image Type

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.

Details

FSTDDEV applies a standard deviation speckle filter on a SAR image. It is designed to smooth out noise while retaining edges or shape features in the image.

Different filter sizes will greatly affect the quality of processed images. If the filter is too small, the noise filtering algorithm is not effective. If the filter is too large, subtle details of the image will be lost in the filtering process. A 7x7 filter usually gives the best results.

The standard deviation filter model requires that the signal represent power. If the input image is in amplitude format, each pixel value will be squared to derive power, and the square root will be applied to the filtered result so that the output still has amplitude values.

Algorithm

FSTDDEV performs spatial filtering on each individual pixel in an image using the gray-level values in a square window surrounding each pixel. The values for the filter size must be odd integers, and can be 1 to 33 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 = (Sum2 - nValidPixelsInWindow*Mean2)/( nValidPixelsInWindow -1)

where:

Sum2 = Addition of squares of valid pixels in a window.
nValidPixelsInWindow = Number of valid pixels in a window.
Mean2 = Square of the mean value in a window.

References

Jong-Sen Lee, "Digital Image Enhancement and Noise Filtering by Use of Local Statistics", IEEE Transactions on Pattern Analysis and Machine Intelligence , Vol. PAM1-2, No. 2, March, 1980.

J.S.Lee, "Refined Filtering of Image Noise Using Local Statistics" Computer Graphic and Image Processing 15, 380-389 (1981)

D.T. Kuan, A.A. Sawchuk, T.C. Strand, and P. Chavel, "Adaptive restoration of images with speckle," IEEE Trans. ASSP., Vol. 35, no. 3, pp. 373-383, March 1987.

A. Lopes, R. Touzi and E. Nezry, "Adaptive speckle filters and Scene heterogeneity", IEEE Transaction on Geoscience and Remote Sensing , Vol. 28, No. 6, pp. 992-1000, Nov. 1990.

V.S. Frost, J.A. Stiles, K.S. Shanmugan, and J.C. Holtzman, "A model for radar images and its application to adaptive digital filtering of multiplicative noise," IEEE Trans. Pattern AnalysisThe and Machine Intelligence , vol. 4, no. 2, pp. 157-166, March 1982.

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.