Help Content > Basic Module > Intensity Processing > Filtering

Purpose

Images obtained from coherent sensors such as SAR (or Laser) system are characterized by speckle, This is a spatially random multiplicative noise due to coherent superposition of multiple backscatter sources within a SAR resolution element. In other words, speckle is a statistical fluctuation associated with the radar reflectivity of each pixel a scene. A first step to reduce the speckle - at the expense of spatial resolution - is usually performed during the multi-looking, where range and/or azimuth resolution cells are averaged.

Whenever two or more images of the same scene taken at different times are available, multi-temporal speckle filtering – which exploits the space-varying temporal correlation of speckle between the images – should be applied, in order to reduce this system inherent multiplicative noise.

Technical Note

De Grandi Filter

It has to be pointed out that this multi-temporal filtering is based on the assumption that the same resolution element on the ground is illuminated by the radar beam in the same way, and corresponds to the same co-ordinates in the image plane (sampled signal) in all images of the time series. In other words the SAR geometry is the same for all acquisitions. The reflectivity can of course change from one time to the next due to a change in the dielectric and geometrical properties of the elementary scatters, but should not change due to a different position of the resolution element with respect to the radar. Therefore proper spatial coregistration of the SAR images in the time series is condition sine qua non and of paramount importance.

For what concerns the ENL setting, it is suggested to leave it as default (i.e. -1) for single look data; vice versa in case of multilook data it is better to estimate it on a homogeneous area of the image.

The Coregistration step must be performed prior the execution of this filter. Input data must be in the satellite view geometry; geocoded (_geo) data are not admitted.

The filter works in a combined time-space domain. Each element in homogeneous areas with developed speckle is averaged with corresponding uncorrelated elements in the time-series. The mean values of the probability distribution function of each instance in the averaged series is adjusted to keep track of changes in reflectivity. The adjustment is performed in space by estimation in a diagonal wavelet basis of the local mean backscatter values in each data set. Since the wavelet based estimator preserves structures in the image (such as edges and point targets), these structures (and changes thereof) are also preserved (and denoised) by the time domain averaging.

The constrained version of the filter is an extended version of the already very effective multi-temporal De Grandi filter, developed to enhance temporal and spatial variations when a large number of observations over time is available, i.e. in case of large time-series. This approach should also be preferred in case of applications aiming the identification of relevant changes over time (i.e. change/target detection).

The constrained approach emphasizes single-date statistics and object variations by analysing the single-date Wavelet Thresholded files, which basically are heavily speckle-filtered files. Whenever the object analysed shows little-to no temporal stationarity, a different filtering strategy is applied following the single-date image properties. Ultimately, a Gamma or a Frost filtering approach (depending on the relative module licensing) is performed on critical objects/areas, enhancing their unique temporal properties.

The current filter is a variant of the one proposed in:

G. F. De Grandi, M. Leysen, J. S. Lee, and D. Schuler, “Radar reflectivity estimation using multiple SAR scenes of the same target: Technique and applications,” in Proc. IEEE Int. Remote Sens. Sci. Vis. Sustain. Develop. Geosci. Remote Sens. (IGARSS’97), Aug. 3–8, 1997, vol. 2, pp. 1047–1050.

Input Files

Input file list

Input file names of coregistered (_pwr, _rsp) or ground (_gr) data. This file list is mandatory.

Parameters - Principal Parameters

Do differential

If false, the process is carried only on the maximum common area. NaN will be propagated throughout the time series.

If true, the common area is filtered using the total number of images, the other part of images are proportionally filtered base on the number of images available for that area. For this reason, NaN are not propagated.

Incremental Option (not available for the ITS Workflow)

If set to true the software will perform incremental processing. The ''Incremental Option'' field has to be set on true during both the ''first processing'' and during the ''second'' one, while the new images are being added. The ''Incremental Option'' will create a folder named ''incremental'', located in the output folder, that will contains all the intermediate results needed to compute the incremental De Grandi filter.

To run an incremental De Grandi filtering, the following steps need to be performed:

•Import the new images and put them in the folder with the older ones

•Multilook the new images

•Coregister the entire datastack: new images + old images

•Apply the De Grandi filter on the whole datastack, and select as output folder the one used for the first processing, doing so the De Grandi algorithm will act only on the new images.

Apply Constrains

If set to false, the standard De Grandi Multi-temporal filter will be performed. Temporal constrains will be applied otherwise.

Minimum Temporal frequency (Apply Constrains=True)

If one same object does not appear in all the images but only in a subset of them, a different filtering behavior can be applied according to the frequency of its appearances.

If the object appears with a lower frequency than the minimum temporal frequency, the object is filtered by means of a spatial filter (such as Gamma or Frost).

If the object appears with a higher frequency than the minimum temporal frequency, the object is filtered by means of a temporal filter and only the images where the object appears are used for the filtering.

Maximum variation (dB)(Apply Constrains=True)

Maximum change threshold allowed for one same object to be considered stable. If one same object signal response changes by more than the specified threshold between different images, the object is considered as changed/different.

Keep Wavelet Thresholded files

If set to true, intermediate single date filtered images will be included in the output.

Parameters - Global

It brings to the general section of the Preferences parameters. Any modified value will be used and stored for further processing sessions.

Parameters - Other Parameters

It brings to the general section of the Preferences parameters. Any modified value will be used and stored for further processing sessions.

Equivalent Number of Looks (ENL)

The Equivalent Number of Looks is equivalent to the number of independent Intensity values averaged per pixel during the multi-looking process. This parameter can be easily estimated over a homogeneous (stationary) sample in the input Intensity data according to:

ENL = mean2 / standard deviation2

In case that ENL is not set, the Number of Looks (NL) used during the multi-looking process is considered.

Note that, to tune the strength of speckle filtering and the level of preservation of scene details, it is preferable to adjust the value of the ENL, rather than to change the size of the processing window:

•To reduce the strength of speckle filtering, with the aim to preserve the thinnest details of the scene, enter a ENL value slightly higher than the calculated one;

•Inversely, to improve the filtering of the speckle (possibly at the cost of the thinnest details of the scene), enter a ENL value slightly lower than the calculated one.

Output Files

If the incremental processing is applied (Apply Incremental field set on true), the output folder must be the same one set for the previous filtering processing. This will allow the software to locate the intermediate folder.

Output file list

Output file list of the filtered data. This file list is mandatory.

_fil

Filtered Intensity image and associated header files (.sml, .hdr).

_meta

It allows to load the processing results as a single file.

Details specific to the Units of Measure and Nomenclature of the output products can be found in the Data Format section.

General Functions

Exec

The processing step is executed.

Store Batch

The processing step is stored in the batch list. The Batch Browser button allows to load the batch processing list.

The window will be closed.

Help

Specific help document section.

Specific Function(s)

None.

Basic Module - Intensity Processing - Filtering - De Grandi Spatio-Temporal Filtering

Basic Module - Intensity Processing - Filtering - De Grandi Spatio-Temporal Filtering