Speckle function

Overview

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

Parameter	Description
Raster	The input raster.
Filter Type	Specifies the filter type to be used in the smoothing algorithm to remove speckle noise: Lee—A spatial filter will be applied to each pixel in an image to reduce the speckle noise. This option filters the data based on local statistics calculated within a square window. This filter is useful for smoothing speckled data that has an additive or multiplicative component. This is the default. Enhanced Lee—A spatial filter that preserves the sharpness and detail of the image while reducing the speckle noise. This option is an enhanced version of the Lee filter, which is useful for reducing speckle while preserving texture information. Frost—An exponentially damped circularly symmetric filter that uses local statistics within individual filter windows to reduce the speckle noise. This does not affect image features at the edges. This filter is useful for reducing speckle while preserving edges. Kuan—A spatial filter, the Kuan filter, will be applied to each pixel in an image to reduce the speckle noise. It filters the data based on local statistics of the centered pixel value that is calculated using neighboring pixels. This filter is useful for reducing speckle while preserving edges. Gamma MAP—A Bayesian analysis and gamma distribution filter will be applied to reduce the speckle noise. This filter is useful for reducing speckle while preserving edges. Refined Lee—A spatial filter will be applied to selected pixels, based on local statistics, to reduce the speckle noise. This filter uses a nonsquare filter window to match the direction of edges. It is useful for reducing speckle while preserving edges.
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.