Speckle function

The Speckle function removes speckle in radar datasets and smooths the grainy salt and pepper effect, while retaining edges and sharp features in the image. Speckle is the inherent condition that is a result of constructive and destructive interference of the backscattered signal. The images generated by laser, ultrasound, and synthetic aperture radar (SAR) systems are subject to speckle noise due to the interference of the returning electromagnetic waves scattered from multiple surfaces. The Speckle function uses mathematical models to filter the bright and dark spots that are generated as a result of interference, to allow better image interpretation.

Notes

Smoothing algorithms in the Speckle function reduce and filter speckle using the Lee, Enhanced Lee, Frost, Kuan, Gamma MAP, and Refined Lee filter types.

For optimal speckle reduction, you can try the following:

  • Filter Size greatly affects the quality of processed images. A 7-by-7 filter usually gives good results with moderate smoothing.
  • Number of Looks is used to estimate noise variance, and it effectively controls the amount of smoothing applied to the image by the filter. A smaller value leads to more smoothing; a larger value preserves more distinct image features.
  • Apply a histogram stretch to adjust the contrast or brightness of the image.

Parameters

ParameterDescription

Raster

The input raster.

Filter Type

Specifies the filter type to be used in the smoothing algorithm to remove speckle noise:

Filter Size

Specifies the size of the pixel window used to filter noise:

  • 3x3
  • 5x5
  • 7x7
  • 9x9
  • 11x11
The default is 3x3.

Noise Model

Specifies the type of noise that is reducing the quality of the radar image:

  • Multiplicative Noise—Random signal noise that is multiplied into the relevant signal during capture or transmission
  • Additive Noise—Random signal noise that is added into the relevant signal during capture or transmission
  • Additive and Multiplicative Noise—Both noise models
This parameter is only valid when Filter Type is set to Lee. The default is Multiplicative Noise.

Noise Variance

Specifies the noise variance of the radar image.

This parameter is only valid when Filter Type is set to Lee and Noise Model is set to Additive Noise or Additive and Multiplicative Noise. The default value is 0.25.

Additive Noise Mean

Specifies the mean value of additive noise. A larger noise mean value will produce less smoothing, while a smaller value results in more smoothing.

This parameter is only valid when Filter Type is set to Lee and Noise Model is set to Additive and Multiplicative Noise. The default value is 0.

Multiplicative Noise Mean

Specifies the mean value of multiplicative noise. A larger noise mean value will produce less smoothing, while a smaller value results in more smoothing.

This parameter is only valid when Filter Type is set to Lee and Noise Model is set to Multiplicative Noise or Additive and Multiplicative Noise. The default value is 1.

Number of Looks

Specifies the number of looks of the image, which controls image smoothing and estimates noise variance. A smaller value results in more smoothing, while a larger value retains more image features.

This parameter is only valid when Filter Type is set to Lee and Noise Model is set to Multiplicative Noise, or when Filter Type is set to Enhanced Lee, Kuan, Gamma MAP. The default value is 1.

Damping Factor

Specifies the extent of exponential damping effect on filtering. A larger damping value preserves edges better but smooths less, while a smaller value produces more smoothing. A value of 0 results in the same output as a low-pass filter.

This parameter is only valid when Filter Type is set to Enhanced Lee or Frost. The default value is 1.


In this topic
  1. Notes
  2. Parameters