Speckle

摘要

通过移除斑点并消除雷达数据集中的噪声，并在影像中保留边和尖锐要素来创建栅格对象。

说明

有关此函数工作原理的更多信息，请参阅斑点栅格函数。

栅格对象所引用的栅格数据集是临时性的。 要将其设置为永久，可以调用栅格对象的 save 方法。

语法

Speckle (raster, {filter_type}, {filter_size}, {noise_model}, {noise_var}, {additive_noise_mean}, {multiplicative_noise_mean}, {nlooks}, {damp_factor})

参数	说明	数据类型
raster	The input raster.	Raster
filter_type	Specifies the filter type that will be used in the smoothing algorithm to remove speckle noise. Lee—The Lee filter will be used, which reduces the speckle noise by applying a spatial filter to each pixel in an image and filters the data based on local statistics calculated within a square window. EnhancedLee—The EnhancedLee filter will be used, which is a refined version of the Lee filter that reduces the speckle noise effectively by preserving image sharpness and detail. This filter requires the damp_factor and nlooks arguments to be set. Frost—The Frost filter will be used, which reduces speckle noise and preserves important image features at the edges with an exponentially damped circularly symmetric filter that uses local statistics within individual filter windows. This filter requires the damp_factor argument to be set. Kuan—The Kuan filter will be used, which follows a similar filtering process to the Lee filter in reducing speckle noise. This filter also applies a spatial filter to each pixel in an image, filtering the data based on local statistics of the centered pixel value that is calculated using the neighboring pixels. The Kuan filter requires the nlooks argument to be set, which controls image smoothing and estimates noise variance. Gamma MAP—A Bayesian analysis and gamma distribution filter will be used 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. (默认值为 Lee)	String
filter_size	Specifies the size of the filter window in pixels. 3x3—The pixel size of the filter window is 3 by 3. 5x5—The pixel size of the filter window is 5 by 5. 7x7—The pixel size of the filter window is 7 by 7. 9x9—The pixel size of the filter window is 9 by 9. 11x11—The pixel size of the filter window is 11 by 11. (默认值为 3x3)	String
noise_model	Specifies the type of noise that is reducing the quality of the radar image. This argument is only valid when the filter_type argument is set to Lee. Multiplicative—Random signal noise that is multiplied into the relevant signal during capture or transmission is reducing the quality of the image. Additive—Random signal noise that is added into the relevant signal during capture or transmission is reducing the quality of the image. AdditiveAndMultiplicative—A combination of both noise models is reducing the quality of the image. (默认值为 Multiplicative)	String
noise_var	The noise variance of the radar image. This argument is only valid when the filter_type argument is set to Lee and the noise_model argument is set to Additive or AdditiveAndMultiplicative. (默认值为 None)	Double
additive_noise_mean	The mean value of additive noise. A larger noise mean value will produce less smoothing, while a smaller value results in more smoothing. This argument is only valid when the filter_type argument is set to Lee and the noise_model argument is set to Additive or AdditiveAndMultiplicative. (默认值为 None)	Double
multiplicative_noise_mean	The mean value of multiplicative noise. A larger noise mean value will produce less smoothing, while a smaller value results in more smoothing. This argument is only valid when the filter_type argument is set to Lee and the noise_model argument is set to Multiplicative or AdditiveAndMultiplicative. (默认值为 1)	Double
nlooks	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 argument is only valid when the filter_type argument is set to Lee and the noise_model argument is set to Multiplicative, or when the filter_type argument is set to Kuan. (默认值为 1)	Integer
damp_factor	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. This parameter is only valid when the filter_type argument is set to EnhancedLee or Frost. (默认值为 None)	Double

返回值

数据类型	说明
Raster	输出栅格。

代码示例

斑点示例

将 Lee 滤镜应用于 Sentinel 1 雷达影像。

import arcpy

out_speckle_raster = arcpy.sa.Speckle("Sentinel_1.tif", filter_type="Lee", filter_size="3x3",
                                              noise_model="AdditiveAndMultiplicative", noise_var=0.25,
                                              additive_noise_mean=0, multiplicative_noise_mean=1)